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StegoAppDB: a Steganography Apps Forensics Image DatabaseApr 19 2019In this paper, we present a new reference dataset simulating digital evidence for image steganography. Steganography detection is a digital image forensic topic that is relatively unknown in practical forensics, although stego app use in the wild is on ... More
Semi-Supervised First-Person Activity Recognition in Body-Worn VideoApr 19 2019Body-worn cameras are now commonly used for logging daily life, sports, and law enforcement activities, creating a large volume of archived footage. This paper studies the problem of classifying frames of footage according to the activity of the camera-wearer ... More
Self-Supervised Audio-Visual Co-SegmentationApr 18 2019Segmenting objects in images and separating sound sources in audio are challenging tasks, in part because traditional approaches require large amounts of labeled data. In this paper we develop a neural network model for visual object segmentation and ... More
Deep Optics for Monocular Depth Estimation and 3D Object DetectionApr 18 2019Depth estimation and 3D object detection are critical for scene understanding but remain challenging to perform with a single image due to the loss of 3D information during image capture. Recent models using deep neural networks have improved monocular ... More
Road Crack Detection Using Deep Convolutional Neural Network and Adaptive ThresholdingApr 18 2019Crack is one of the most common road distresses which may pose road safety hazards. Generally, crack detection is performed by either certified inspectors or structural engineers. This task is, however, time-consuming, subjective and labor-intensive. ... More
Fast Single Image Dehazing via Multilevel Wavelet Transform based OptimizationApr 18 2019The quality of images captured in outdoor environments can be affected by poor weather conditions such as fog, dust, and atmospheric scattering of other particles. This problem can bring extra challenges to high-level computer vision tasks like image ... More
Do Lateral Views Help Automated Chest X-ray Predictions?Apr 17 2019Most convolutional neural networks in chest radiology use only the frontal posteroanterior (PA) view to make a prediction. However the lateral view is known to help the diagnosis of certain diseases and conditions. The recently released PadChest dataset ... More
Extending time-domain ptychography to generalized phase-only transfer functionsApr 17 2019We extend the time-domain ptychographic iterative engine to generalized spectral phase-only transfer functions. The modified algorithm, i$^2$PIE, is described and its robustness is demonstrated by different numeric simulations. The concept is experimentally ... More
CloudSegNet: A Deep Network for Nychthemeron Cloud Image SegmentationApr 16 2019We analyze clouds in the earth's atmosphere using ground-based sky cameras. An accurate segmentation of clouds in the captured sky/cloud image is difficult, owing to the fuzzy boundaries of clouds. Several techniques have been proposed that use color ... More
Convolutional Neural Networks for Classification of Alzheimer's Disease: Overview and Reproducible EvaluationApr 16 2019In the past two years, over 30 papers have proposed to use convolutional neural network (CNN) for AD classification. However, the classification performances across studies are difficult to compare. Moreover, these studies are hardly reproducible because ... More
ASD-DiagNet: A hybrid learning approach for detection of Autism Spectrum Disorder using fMRI dataApr 16 2019Mental disorders such as Autism Spectrum Disorders (ASD) are heterogeneous disorders that are notoriously difficult to diagnose, especially in children. The current psychiatric diagnostic process is based purely on the behavioural observation of symptomology ... More
fMRI Based Cerebral Instantaneous Parameters for Automatic Alzheimer's, Mild Cognitive Impairment and Healthy Subject ClassificationApr 16 2019Automatic identification and categorization of Alzheimer's patients and the ability to distinguish between different levels of this disease can be very helpful to the research community in this field, since other non-automatic approaches are very time-consuming ... More
Multi-Branch Tensor Network Structure for Tensor-Train Discriminant AnalysisApr 15 2019Higher-order data with high dimensionality arise in a diverse set of application areas such as computer vision, video analytics and medical imaging. Tensors provide a natural tool for representing these types of data. Although there has been a lot of ... More
Beam Profiler Network (BPNet) -- A Deep Learning Approach to Mode Demultiplexing of Laguerre-Gaussian Optical BeamsApr 14 2019The transverse field profile of light is being recognized as a resource for classical and quantum communications for which reliable methods of sorting or demultiplexing spatial optical modes are required. Here, we demonstrate, experimentally, state-of-the-art ... More
Geometry of the EOS(R) Radiographic ScannerApr 14 2019The EOS(R) scanner is a radiographic system that captures PA and lateral images in standing posture. The system is widely used in diagnosis and assessment of scoliosis, as it provides a low-dose alternative to traditional X-ray and can capture full-body ... More
Automatic Target Detection for Sparse Hyperspectral ImagesApr 14 2019This chapter introduces a novel target detector for hyperspectral imagery. The detector is independent on the unknown covariance matrix, behaves well in large dimensions, distributional free, invariant to atmospheric effects, and does not require a background ... More
All-optical naked-eye ghost imagingApr 13 2019Ghost imaging is usually based on optoelectronic process and eletronic computing. We here propose a new ghost imaging scheme, which avoids any optoelectronic or electronic process. Instead, the proposed scheme exploits all-optical correlation via the ... More
Naked-Eye Ghost Imaging via Photoelectric-FeedbackApr 13 2019Based on optical correlations, ghost imaging is usually reconstructed by computer algorithm from the acquired data. We here proposed an alternatively high contrast naked-eye ghost imaging scheme which avoids computer algorithm processing. Instead, the ... More
YouTube UGC Dataset for Video Compression ResearchApr 13 2019Non-professional video, commonly known as User Generated Content (UGC) has become very popular in today's video sharing applications. However, there are few public UGC datasets available for video compression and quality assessment research. This paper ... More
Boundary-Preserved Deep Denoising of the Stochastic Resonance Enhanced Multiphoton ImagesApr 12 2019Apr 15 2019As the rapid growth of high-speed and deep-tissue imaging in biomedical research, it is urgent to find a robust and effective denoising method to retain morphological features for further texture analysis and segmentation. Conventional denoising filters ... More
Real-Time Dense Stereo Embedded in A UAV for Road InspectionApr 12 2019The condition assessment of road surfaces is essential to ensure their serviceability while still providing maximum road traffic safety. This paper presents a robust stereo vision system embedded in an unmanned aerial vehicle (UAV). The perspective view ... More
Enhancing Bridge Deck Delamination Detection Based on Aerial Thermography Through Grayscale Morphologic Reconstruction: A Case StudyApr 11 2019Environmental-induced temperature variations across the bridge deck were one of the major factors that degraded the performance of delamination detection through thermography. The non-uniformly distributed thermal background yields the assumption of most ... More
Retinal Vessels Segmentation Based on Dilated Multi-Scale Convolutional Neural NetworkApr 11 2019Accurate segmentation of retinal vessels is a basic step in Diabetic retinopathy(DR) detection. Most methods based on deep convolutional neural network (DCNN) have small receptive fields, and hence they are unable to capture global context information ... More
CNN-Based Deep Architecture for Reinforced Concrete Delamination Segmentation Through ThermographyApr 11 2019Delamination assessment of the bridge deck plays a vital role for bridge health monitoring. Thermography as one of the nondestructive technologies for delamination detection has the advantage of efficient data acquisition. But there are challenges on ... More
Two-Step phase estimation using the Simplified Lissajous Ellipse Fitting method with Gabor filter banks preprocessingApr 10 2019We present the Simplified Lissajous Ellipse Fitting (SLEF) method for the calculation of the random phase step and the phase distribution from two phase-shifted interferograms. We consider interferograms with spatial and temporal dependency of background ... More
Scanner Invariant Representations for Diffusion MRI HarmonizationApr 10 2019Pooled imaging data from multiple sources is subject to variation between the sources. Correcting for these biases has become incredibly important as the size of imaging studies increases and the multi-site case becomes more common. We propose learning ... More
Diagnosis of Celiac Disease and Environmental Enteropathy on Biopsy Images Using Color Balancing on Convolutional Neural NetworksApr 10 2019Celiac Disease (CD) and Environmental Enteropathy (EE) are common causes of malnutrition and adversely impact normal childhood development. CD is an autoimmune disorder that is prevalent worldwide and is caused by an increased sensitivity to gluten. Gluten ... More
Motion correction in cardiac perfusion data by using robust matrix decompositionApr 10 2019Motion free reconstruction of compressively sampled cardiac perfusion MR images is a challenging problem. It is due to the aliasing artifacts and the rapid contrast changes in the reconstructed perfusion images. In addition to the reconstruction limitations, ... More
Regularized Inverse Holographic Volume Reconstruction for 3D Particle TrackingApr 09 2019The key limitations of digital inline holography (DIH) for particle tracking applications are poor longitudinal resolution, particle concentration limits, and case-specific processing. We utilize an inverse problem method with fused lasso regularization ... More
Efficient Reconstruction of Free Breathing Under-Sampled Cardiac Cine MRIApr 09 2019Respiratory motion can cause strong blurring artifacts in the reconstructed image during MR acquisition. These artifacts become more prominent when use in the presence of undersampled data. Recently, compressed sensing (CS) is developed as an MR reconstruction ... More
Tracking-free Determination of Microparticle Motion from Image VarianceApr 09 2019In this work, we use the standard deviation of image pixel intensity to analyse the speed, direction and surface-interaction of microparticles in fluid. First, we present an analytical model for estimating the total variance in the image space for directed ... More
Hierarchical Deep Feature Learning For Decoding Imagined Speech From EEGApr 08 2019We propose a mixed deep neural network strategy, incorporating parallel combination of Convolutional (CNN) and Recurrent Neural Networks (RNN), cascaded with deep autoencoders and fully connected layers towards automatic identification of imagined speech ... More
Data-Driven Design for Fourier Ptychographic MicroscopyApr 08 2019Fourier Ptychographic Microscopy (FPM) is a computational imaging method that is able to super-resolve features beyond the diffraction-limit set by the objective lens of a traditional microscope. This is accomplished by using synthetic aperture and phase ... More
Deep Learning Based Computed Tomography Whys and WhereforesApr 08 2019This is an article about the Computed Tomography (CT) and how Deep Learning influences CT reconstruction pipeline, especially in low dose scenarios.
Spectral Variability Aware Blind Hyperspectral Image Unmixing Based on Convex GeometryApr 08 2019Hyperspectral image unmixing has proven to be a useful technique to interpret hyperspectral data, and is a prolific research topic in the community. Most of the approaches used to perform linear unmixing are based on convex geometry concepts, because ... More
Extreme Image Compression via Multiscale Autoencoders With Generative Adversarial OptimizationApr 08 2019We propose a MultiScale AutoEncoder(MSAE) based extreme image compression framework to offer visually pleasing reconstruction at a very low bitrate. Our method leverages the "priors" at different resolution scale to improve the compression efficiency, ... More
Planar Geometry and Latest Scene Recovery from a Single Motion Blurred ImageApr 07 2019Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the case of 3D scenes ... More
Planar Geometry and Latest Scene Recovery from a Single Motion Blurred ImageApr 07 2019Apr 15 2019Existing works on motion deblurring either ignore the effects of depth-dependent blur or work with the assumption of a multi-layered scene wherein each layer is modeled in the form of fronto-parallel plane. In this work, we consider the case of 3D scenes ... More
Deep Learning Enabled Real Time Speckle Recognition and Hyperspectral Imaging using a Multimode Fiber ArrayApr 07 2019We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral transmission matrix. ... More
Artificial Intelligence for Pediatric OphthalmologyApr 06 2019PURPOSE OF REVIEW: Despite the impressive results of recent artificial intelligence (AI) applications to general ophthalmology, comparatively less progress has been made toward solving problems in pediatric ophthalmology using similar techniques. This ... More
Deep Learning-based Universal Beamformer for Ultrasound ImagingApr 05 2019In ultrasound (US) imaging, individual channel RF measurements are back-propagated and accumulated to form an image after applying specific delays. While this time reversal is usually implemented using a hardware- or software-based delay-and-sum (DAS) ... More
Image Reconstruction: From Sparsity to Data-adaptive Methods and Machine LearningApr 04 2019The field of image reconstruction has undergone four waves of methods. The first wave was analytical methods, such as filtered back-projection (FBP) for X-ray computed tomography (CT) and the inverse Fourier transform for magnetic resonance imaging (MRI), ... More
UU-Nets Connecting Discriminator and Generator for Image to Image TranslationApr 04 2019Adversarial generative model have successfully manifest itself in image synthesis. However, the performance deteriorate and unstable, because discriminator is far stable than generator, and it is hard to control the game between the two modules. Various ... More
Characterising optical fibre transmission matrices using metasurface reflector stacks for lensless imaging without distal accessApr 04 2019Apr 05 2019The ability to form images through hair-thin optical fibres promises to open up new applications from biomedical imaging to industrial inspection. Unfortunately, deployment has been limited because small changes in mechanical deformation (e.g. bending) ... More
Characterising optical fibre transmission matrices using metasurface reflector stacks for lensless imaging without distal accessApr 04 2019The ability to form images through hair-thin optical fibres promises to open up new applications from biomedical imaging to industrial inspection. Unfortunately, deployment has been limited because small changes in mechanical deformation (e.g. bending) ... More
LED illumination faceted Fresnel DOEs generating perceived virtual 3D visionApr 04 2019An approach for the optimization and synthesis of a phase-only faceted Fresnel type diffractive optical element (FDOE) generating 3D virtual images is proposed. The FDOE is a transmissive Fresnel type DOE array, which produces the perception of a customized ... More
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networksApr 04 2019In applications of supervised learning applied to medical image segmentation, the need for large amounts of labeled data typically goes unquestioned. In particular, in the case of brain anatomy segmentation, hundreds or thousands of weakly-labeled volumes ... More
Total Variation and Tight Frame Image Segmentation with Intensity InhomogeneityApr 03 2019Image segmentation is an important task in the domain of computer vision and medical imaging. In natural and medical images, intensity inhomogeneity, i.e. the varying image intensity, occurs often and it poses considerable challenges for image segmentation. ... More
FaceQnet: Quality Assessment for Face Recognition based on Deep LearningApr 03 2019Apr 04 2019In this paper we develop a Quality Assessment approach for face recognition based on deep learning. The method consists of a Convolutional Neural Network, FaceQnet, that is used to predict the suitability of a specific input image for face recognition ... More
FaceQnet: Quality Assessment for Face Recognition based on Deep LearningApr 03 2019In this paper we develop a Quality Assessment approach for face recognition based on deep learning. The method consists of a Convolutional Neural Network, FaceQnet, that is used to predict the suitability of a specific input image for face recognition ... More
FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial AnimationApr 02 2019Facial expression analysis based on machine learning requires large number of well-annotated data to reflect different changes in facial motion. Publicly available datasets truly help to accelerate research in this area by providing a benchmark resource, ... More
Deep Learning Methods for Parallel Magnetic Resonance Image ReconstructionApr 01 2019Following the success of deep learning in a wide range of applications, neural network-based machine learning techniques have received interest as a means of accelerating magnetic resonance imaging (MRI). A number of ideas inspired by deep learning techniques ... More
Spatio-Temporal Deep Learning-Based Undersampling Artefact Reduction for 2D Radial Cine MRI with Limited DataApr 01 2019In this work we reduce undersampling artefacts in two-dimensional ($2D$) golden-angle radial cine cardiac MRI by applying a modified version of the U-net. We train the network on $2D$ spatio-temporal slices which are previously extracted from the image ... More
Comparison of Possibilistic Fuzzy Local Information C-Means and Possibilistic K-Nearest Neighbors for Synthetic Aperture Sonar Image SegmentationApr 01 2019Synthetic aperture sonar (SAS) imagery can generate high resolution images of the seafloor. Thus, segmentation algorithms can be used to partition the images into different seafloor environments. In this paper, we compare two possibilistic segmentation ... More
Ghost imaging LiDAR via sparsity constraints using push-broom scanningApr 01 2019Ghost imaging LiDAR via sparsity constraints using push-broom scanning is proposed. It can image the stationary target scene continuously along the scanning direction by taking advantage of the relative movement between the platform and the target scene. ... More
Machine Vision for Natural Gas Methane Emissions Detection Using an Infrared CameraApr 01 2019It is crucial to reduce natural gas methane emissions, which can potentially offset the climate benefits of replacing coal with gas. Optical gas imaging (OGI) is a widely-used method to detect methane leaks, but is labor-intensive and cannot provide leak ... More
Deep Clustering With Intra-class Distance Constraint for Hyperspectral ImagesApr 01 2019The high dimensionality of hyperspectral images often results in the degradation of clustering performance. Due to the powerful ability of deep feature extraction and non-linear feature representation, the clustering algorithm based on deep learning has ... More
Hermite-Gaussian Mode Detection via Convolution Neural NetworksMar 30 2019Hermite-Gaussian (HG) laser modes are a complete set of solutions to the free-space paraxial wave equation in Cartesian coordinates and represent a close approximation to physically-realizable laser cavity modes. Additionally, HG modes can be mode-multiplexed ... More
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology ImagesMar 29 2019We consider preoperative prediction of thyroid cancer based on ultra-high-resolution whole-slide cytopathology images. Inspired by how human experts perform diagnosis, our approach first identifies and classifies diagnostic image regions containing informative ... More
Motion artifact removal and signal enhancement to achieve in vivo dynamic full field OCTMar 29 2019We present a filtering procedure based on singular value decomposition to remove artifacts arising from sample motion during dynamic full field OCT acquisitions. The presented method succeeded in removing artifacts created by environmental noise from ... More
A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural NetworkMar 29 2019Data scarcity has refrained deep learning models from making greater progress in prostate images analysis using multiparametric MRI. In this paper, an efficient convolutional neural network (CNN) was developed to classify lesion malignancy for prostate ... More
A Deep Dive into Understanding Tumor Foci Classification using Multiparametric MRI Based on Convolutional Neural NetworkMar 29 2019Apr 04 2019Data scarcity has refrained deep learning models from making greater progress in prostate images analysis using multiparametric MRI. In this paper, an efficient convolutional neural network (CNN) was developed to classify lesion malignancy for prostate ... More
Is multiplexed off-axis holography for quantitative phase imaging more spatial bandwidth-efficient than on-axis holography?Mar 28 2019Digital holographic microcopy is a thriving imaging modality that attracts considerable research interest due to its ability to not only create excellent label-free contrast, but also supply valuable physical information regarding the density and dimensions ... More
When topological derivatives met regularized Gauss-Newton iterations in holographic 3D imagingMar 28 2019We propose an automatic algorithm for 3D inverse electromagnetic scattering based on the combination of topological derivatives and regularized Gauss-Newton iterations. The algorithm is adapted to decoding digital holograms. A hologram is a two-dimensional ... More
Field-portable quantitative lensless microscopy based on translated speckle illumination and sub-sampled ptychographic phase retrievalMar 28 2019We report a compact, cost-effective and field-portable lensless imaging platform for quantitative microscopy. In this platform, the object is placed on top of an image sensor chip without using any lens. We use a low-cost galvo scanner to rapidly scan ... More
Spectral Unmixing: A Derivation of the Extended Linear Mixing Model from the Hapke ModelMar 28 2019In hyperspectral imaging, spectral unmixing aims at decomposing the image into a set of reference spectral signatures corresponding to the materials present in the observed scene and their relative proportions in every pixel. While a linear mixing model ... More
Radiological images and machine learning: trends, perspectives, and prospectsMar 27 2019The application of machine learning to radiological images is an increasingly active research area that is expected to grow in the next five to ten years. Recent advances in machine learning have the potential to recognize and classify complex patterns ... More
Stable prediction with radiomics dataMar 27 2019Motivation: Radiomics refers to the high-throughput mining of quantitative features from radiographic images. It is a promising field in that it may provide a non-invasive solution for screening and classification. Standard machine learning classification ... More
Single-pixel imaging with origami pattern constructionMar 27 2019Single-pixel compressive imaging can recover images from a small amount of measurements, offering many benefits especially for the scenes where the array detection is unavailable. However, the widely used random patterns fail to explore internal relations ... More
Super sub-Nyquist single-pixel imaging by means of cake-cutting Hadamard basis sortMar 27 2019Single-pixel imaging via compressed sensing can reconstruct high-quality images from a few linear random measurements of an object/scene known a priori to be sparse or compressive, by using a point/bucket detector without spatial resolution. Nevertheless, ... More
Imaging cytometry without image reconstruction (ghost cytometry)Mar 27 2019Imaging and analysis of many single cells hold great potential in our understanding of heterogeneous and complex life systems and in enabling biomedical applications. We here introduce a recently realized image-free "imaging" cytometry technology, which ... More
Sparse dictionary learning for 2D Kendall shapesMar 27 2019We propose a novel sparse dictionary learning method for planar shapes in the sense of Kendall, i.e., configurations of landmarks in the plane considered up to similitudes. Our shape dictionary method provides a good trade-off between algorithmic simplicity ... More
Colorectal cancer diagnosis from histology images: A comparative studyMar 27 2019Mar 28 2019Computer-aided diagnosis (CAD) based on histopathological imaging has progressed rapidly in recent years with the rise of machine learning based methodologies. Traditional approaches consist of training a classification model using features extracted ... More
On evaluating CNN representations for low resource medical image classificationMar 26 2019Convolutional Neural Networks (CNNs) have revolutionized performances in several machine learning tasks such as image classification, object tracking, and keyword spotting. However, given that they contain a large number of parameters, their direct applicability ... More
Hieroglyph: Hierarchical Glia Graph Skeletonization and MatchingMar 26 2019Automatic 3D reconstruction of glia morphology is a powerful tool necessary for investigating the role of microglia in neurological disorders in the central nervous system. Current glia skeleton reconstruction techniques fail to capture an accurate tracing ... More
What does AI see? Deep segmentation networks discover biomarkers for lung cancer survivalMar 26 2019Non-small-cell lung cancer (NSCLC) represents approximately 80-85% of lung cancer diagnoses and is the leading cause of cancer-related death worldwide. Recent studies indicate that image-based radiomics features from positron emission tomography-computed ... More
Cross-Modal Data Programming Enables Rapid Medical Machine LearningMar 26 2019Labeling training datasets has become a key barrier to building medical machine learning models. One strategy is to generate training labels programmatically, for example by applying natural language processing pipelines to text reports associated with ... More
Data-Driven Microstructure Property RelationsMar 26 2019Apr 01 2019An image based prediction of the effective heat conductivity for highly heterogeneous microstructured materials is presented. The synthetic materials under consideration show different inclusion morphology, orientation, volume fraction and topology. The ... More
Data-Driven Microstructure Property RelationsMar 26 2019An image based prediction of the effective heat conductivity for highly heterogeneous microstructured materials is presented. The synthetic materials under consideration show different inclusion morphology, orientation, volume fraction and topology. The ... More
Spatially-Adaptive Residual Networks for Efficient Image and Video DeblurringMar 25 2019In this paper, we address the problem of dynamic scene deblurring in the presence of motion blur. Restoration of images affected by severe blur necessitates a network design with a large receptive field, which existing networks attempt to achieve through ... More
Spatially-Adaptive Residual Networks for Efficient Image and Video DeblurringMar 25 2019Mar 29 2019In this paper, we address the problem of dynamic scene deblurring in the presence of motion blur. Restoration of images affected by severe blur necessitates a network design with a large receptive field, which existing networks attempt to achieve through ... More
DeepRED: Deep Image Prior Powered by REDMar 25 2019Inverse problems in imaging are extensively studied, with a variety of strategies, tools, and theory that have been accumulated over the years. Recently, this field has been immensely influenced by the emergence of deep-learning techniques. One such contribution, ... More
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural NetworksMar 25 2019Magnetic resonance imaging (MRI) is widely used in clinical practice for visualizing both biological structure and function, but its use has been traditionally limited by its slow data acquisition. Recent advances in compressed sensing (CS) techniques ... More
Temporal phase unwrapping using deep learningMar 23 2019The multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection profilometry (FPP), is capable of eliminating the phase ambiguities even in the presence of surface discontinuities or spatially ... More
Temporal phase unwrapping using deep learningMar 23 2019Mar 28 2019The multi-frequency temporal phase unwrapping (MF-TPU) method, as a classical phase unwrapping algorithm for fringe projection profilometry (FPP), is capable of eliminating the phase ambiguities even in the presence of surface discontinuities or spatially ... More
ADMM-IDNN: Iteratively Double-reweighted Nuclear Norm Algorithm for Group-prior based Nonconvex Compressed Sensing via ADMMMar 23 2019Group-prior based regularization method has led to great successes in various image processing tasks, which can usually be considered as a low-rank matrix minimization problem. As a widely used surrogate function of low-rank, the nuclear norm based convex ... More
Use of Ghost Cytometry to Differentiate Cells with Similar Gross Morphologic CharacteristicsMar 22 2019Imaging flow cytometry shows significant potential for increasing our understanding of heterogeneous and complex life systems and is useful for biomedical applications. Ghost cytometry is a recently proposed approach for directly analyzing compressively ... More
A lightweight convolutional neural network for image denoising with fine details preservation capabilityMar 22 2019Image denoising is a fundamental problem in image processing whose primary objective is to remove the noise while preserving the original image structure. In this work, we proposed a new architecture for image denoising. We have used several dense blocks ... More
A resnet-based universal method for speckle reduction in optical coherence tomography imagesMar 22 2019In this work we propose a ResNet-based universal method for speckle reduction in optical coherence tomography (OCT) images. The proposed model contains 3 main modules: Convolution-BN-ReLU, Branch and Residual module. Unlike traditional algorithms, the ... More
Deep Radiomics for Brain Tumor Detection and Classification from Multi-Sequence MRIMar 21 2019Glioma constitutes 80% of malignant primary brain tumors and is usually classified as HGG and LGG. The LGG tumors are less aggressive, with slower growth rate as compared to HGG, and are responsive to therapy. Tumor biopsy being challenging for brain ... More
Common lines ab-initio reconstruction of $D_2$-symmetric moleculesMar 21 2019Cryo-electron microscopy is a state-of-the-art method for determining high-resolution three-dimensional models of molecules, from their two-dimensional projection images taken by an electron microscope. A crucial step in this method is to determine a ... More
PRNU-Based Source Device Attribution for Highly Compressed YouTube VideosMar 21 2019Photo Response Non-Uniformity (PRNU) is a camera imaging sensor imperfection which has earned a great interest for source device attribution of digital videos. The majority of recent researches about PRNU-based source device attribution for digital videos ... More
PRNU-Based Source Device Attribution for YouTube VideosMar 21 2019Apr 01 2019Photo Response Non-Uniformity (PRNU) is a camera imaging sensor imperfection which has earned a great interest for source device attribution of digital videos. A majority of recent researches about PRNU-based source device attribution for digital videos ... More
Towards a Forensic Event Ontology to Assist Video Surveillance-based Vandalism DetectionMar 21 2019The detection and representation of events is a critical element in automated surveillance systems. We present here an ontology for representing complex semantic events to assist video surveillance-based vandalism detection. The ontology contains the ... More
Individualized Multilayer Tensor Learning with An Application in Imaging AnalysisMar 21 2019This work is motivated by multimodality breast cancer imaging data, which is quite challenging in that the signals of discrete tumor-associated microvesicles (TMVs) are randomly distributed with heterogeneous patterns. This imposes a significant challenge ... More
Dilated deeply supervised networks for hippocampus segmentation in MRIMar 20 2019Tissue loss in the hippocampi has been heavily correlated with the progression of Alzheimer's Disease (AD). The shape and structure of the hippocampus are important factors in terms of early AD diagnosis and prognosis by clinicians. However, manual segmentation ... More
Learning Convolutional Transforms for Lossy Point Cloud Geometry CompressionMar 20 2019Efficient point cloud compression is fundamental to enable the deployment of virtual and mixed reality applications, since the number of points to code can range in the order of millions. In this paper, we present a novel data-driven geometry compression ... More
A Novel Monocular Disparity Estimation Network with Domain Transformation and Ambiguity LearningMar 20 2019Convolutional neural networks (CNN) have shown state-of-the-art results for low-level computer vision problems such as stereo and monocular disparity estimations, but still, have much room to further improve their performance in terms of accuracy, numbers ... More
Photon-Flooded Single-Photon 3D CamerasMar 20 2019Single photon avalanche diodes (SPADs) are starting to play a pivotal role in the development of photon-efficient, long-range LiDAR systems. However, due to non-linearities in their image formation model, a high photon flux (e.g., due to strong sunlight) ... More
Phase-sensitive x-ray ghost imagingMar 20 2019Imaging with hard x-rays is an invaluable tool in medicine, biology, materials science, and cultural heritage. Propagation-based x-ray phase-contrast imaging and tomography have been mostly used to resolve micrometer-scale structures inside weakly absorbing ... More