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Works343 from public data
- 3,951
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- Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance1,319
A statistical view of the texture retrieval problem is presented by combining the two related tasks, namely feature extraction (FE) and similarity measurement (SM), into a joint modeling and classification scheme that leads to a new wavelet-based texture retrieval method that is based on the accurate modeling of the marginal distribution of wavelet coefficients using generalized Gaussian density (GGD).
- Semantic Image Inpainting with Deep Generative Models1,249
A novel method for semantic image inpainting, which generates the missing content by conditioning on the available data, and successfully predicts information in large missing regions and achieves pixel-level photorealism, significantly outperforming the state-of-the-art methods.
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- A Multi-Organ Nucleus Segmentation Challenge558
Several of the top techniques compared favorably to an individual human annotator and can be used with confidence for nuclear morphometrics as well as heavy data augmentation in the MoNuSeg 2018 challenge.
- Efficient Tensor Completion for Color Image and Video Recovery: Low-Rank Tensor Train473
A novel approach to tensor completion, which recovers missing entries of data represented by tensors based on the tensor train (TT) rank, which is able to capture hidden information from tensors thanks to its definition from a well-balanced matricization scheme.
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- Directional multiresolution image representations383
This thesis focuses on the development of new "true" two-dimensional representations for images using a discrete framework that can lead to algorithmic implementations and a new family of block directional and orthonormal transforms based on the ridgelet idea.
- Semantic Image Inpainting with Perceptual and Contextual Losses.372
A novel method for image inpainting based on a Deep Convolutional Generative Adversarial Network that can successfully predict semantic information in the missing region and achieve pixel-level photorealism, which is impossible by almost all existing methods.
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- Framing pyramids317
It is shown that the LP with orthogonal filters is a tight frame, and thus, the optimal linear reconstruction using the dual frame operator has a simple structure that is symmetric with the forward transform.
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- Robust Image and Video Dehazing with Visual Artifact Suppression via Gradient Residual Minimization249
A new method for reliable suppression of different types of visual artifacts in image and video dehazing is proposed and can generate results with much less visual artifacts than previous approaches for lower quality inputs such as compressed video clips.
- Rotation invariant texture characterization and retrieval using steerable wavelet-domain hidden Markov models240
A statistical model for characterizing texture images based on wavelet-domain hidden Markov models that can be easily steered to characterize that texture at any other orientation and obtains a rotation-invariant model of the texture image.
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- SEAGULL: Seam-Guided Local Alignment for Parallax-Tolerant Image Stitching225
A novel structure-preserving warping method is introduced to preserve salient curve and line structures during the warping to substantially improve the effectiveness of this method in dealing with a wide range of challenging images with large parallax.
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- Bayesian Blind Deconvolution with General Sparse Image Priors200
A general method for blind image deconvolution using Bayesian inference with super-Gaussian sparse image priors is presented and theoretical and experimental results demonstrate that the proposed formulation is very effective, efficient, and flexible.
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- Denoising MR Spectroscopic Imaging Data With Low-Rank Approximations165
This paper addresses the denoising problem associated with magnetic resonance spectroscopic imaging (MRSI), where signal-to-noise ratio (SNR) has been a critical problem, and proposes a new scheme that exploits two low-rank structures that exist in MRSI data, one due to partial separability and the other due to linear predictability.
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- Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images164
Novel coding algorithms based on tree-structured segmentation achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme.
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- Signal reconstruction using sparse tree representations119
This work proposes to exploit the tree-structured sparse representation as additional prior information for linear inverse problems with limited numbers of measurements and presents numerical results showing that exploiting the sparse tree representations lead to better reconstruction while requiring less time than methods that only assume sparse representations.
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- Fast Guided Global Interpolation for Depth and Motion102
This work proposes a unified approach that casts the fundamental guided interpolation problem into a hierarchical, global optimization framework, and achieves quantitatively competitive results on various benchmark evaluations, while running much faster than other competing methods designed specifically for either depth upsampling or motion interpolation.
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- CRISP contourlets: a critically sampled directional multiresolution image representation99
A filter bank structure achieving a nonredundant multiresolution and multidirectional expansion of images and can be seen as a critically sampled version of the original contourlet transform, with useful properties including perfect reconstruction, flexible configuration of the number of directions at each scale, and an efficient tree-structured implementation.
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- Automatic Gleason grading of prostate cancer using quantitative phase imaging and machine learning98
This approach will provide a clinically objective and quantitative metric for Gleason grading, allowing us to corroborate results across instruments and laboratories and feed the computer algorithms for improved accuracy.
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- High‐Level Synthesis: Productivity, Performance, and Software Constraints93
An unbiased study of the performance, usability and productivity of HLS using AutoPilot (a state-of-the-art HLS tool), and a case study of stereo matching, an active area of computer vision research that uses techniques also common for image denoising, image retrieval, feature matching, and face recognition.
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- Bilateral Functions for Global Motion Modeling86
This paper uses the bilateral domain to reformulate a piecewise smooth constraint as continuous global modeling constraint and demonstrates how the model can reliably obtain large numbers of good quality correspondences over wide baselines, while keeping outliers to a minimum.
- Image interpolation using multiscale geometric representations85
A novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images and significantly outperforms linear interpolation in subjective quality and in most cases, in terms of PSNR as well.
- RaDICaL: A Synchronized FMCW Radar, Depth, IMU and RGB Camera Data Dataset With Low-Level FMCW Radar Signals80
The ability to go beyond classical radar object detection with the dataset with a classification accuracy of 85.1% using the low-level radar signals captured by the system, supporting the argument that there is value in retaining the information discarded by current radar pipelines.
- Separation of absorption and scattering profiles in spectroscopic optical coherence tomography using a least-squares algorithm79
This paper proposes a least-squares fitting algorithm to separate absorption and scattering profiles when near-infrared absorbing dyes are used, and utilizes the broadband Ti:sapphire laser spectrum together with joint time-frequency analysis.
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- Off-axis quantitative phase imaging processing using CUDA: toward real-time applications72
Real time off-axis Quantitative Phase Imaging is demonstrated using a phase reconstruction algorithm based on NVIDIA’s CUDA programming model that enables the imaging system to support high speed, high throughput, and real-time image acquisition and visualization.
- MCA: A Multichannel Approach to SAR Autofocus68
The MCA approach is found to be computationally efficient and robust and does not require prior assumptions about the SAR scene used in existing methods, and the vector-space formulation of MCA allows sharpness metric optimization to be easily incorporated within the restoration framework as a regularization term.
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- DASC: Robust Dense Descriptor for Multi-Modal and Multi-Spectral Correspondence Estimation59
A novel dense descriptor, called dense adaptive self-correlation (DASC), to estimate dense multi-modal and multi-spectral correspondences and a geometry-invariant DASC (GI-DASC) descriptor that effectively leverages the DASC through a superpixel-based representation is proposed.
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- Integrated Browsing and Searching of Large Image Collections54
This work proposes a multi-modes and integrated image retrieval system that offers the user quick and effective previewing of the collection, intuitive and natural navigating to any parts of it, and query by example or composition for more specific and clearer retrieval goals.
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- Rotation equivariant and invariant neural networks for microscopy image analysis49
This work considers the application of two schemes for encoding rotation equivariance and invariance in a convolutional neural network, namely, the group-equivariant CNN (G-CNN) and a new architecture with simple, efficient conic convolution, for classifying microscopy images.
- Anomaly Detection in Traffic Surveillance Videos with GAN-based Future Frame Prediction44
A semi-supervised method using Generative Adversarial Network trained on regular sequences to predict future frames to detect traffic accidents in traffic videos and a new idea of encoding motion descriptors and scaled intensity loss function to optimize GAN for fast-moving objects is proposed.
- Learning Motion in Feature Space: Locally-Consistent Deformable Convolution Networks for Fine-Grained Action Detection44
A novel locally-consistent deformable convolution is proposed, which utilizes the change in receptive fields and enforces a local coherency constraint to capture motion information effectively to produce features capable of modeling fine-grained motion more efficiently.
- Unsupervised Textual Grounding: Linking Words to Image Concepts44
This work develops a completely unsupervised mechanism for textual grounding using hypothesis testing as a mechanism to link words to detected image concepts.
- Halo-free Phase Contrast Microscopy44
A new approach for retrieving halo-free phase contrast microscopy images by upgrading the conventional PC microscope with an external interferometric module, which generates sufficient data for reversing the halo artifact, which can numerically generate artifact-free PC images.
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- RepMatch: Robust Feature Matching and Pose for Reconstructing Modern Cities43
RepMatch is an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures, based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches.
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- Multimodal Fusion of Imaging and Genomics for Lung Cancer Recurrence Prediction40
By combining computed tomography images and genomics, improved prediction of recurrence is demonstrated using linear Cox proportional hazards models with elastic net regularization and non-linear methods from the neural network literature did not improve performance consistently.
- A smart unmanned aerial vehicle (UAV) based imaging system for inspection of deep hazardous tunnels40
The design and development of a smart UAV platform, Surveyor with Intelligent Rotating Lens (SWIRL), customized for autonomous operation in tunnels, and an innovative rotating system enables undistorted imaging of the tunnel's inner circumference surface using a single camera.
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- Visualizing Escherichia coli Sub-Cellular Structure Using Sparse Deconvolution Spatial Light Interference Tomography38
A label-free method, called deconvolution Spatial Light Interference Tomography (dSLIT), is employed to visualize coiled sub-cellular structures in E. coli cells which are most likely the cytoskeletal MreB protein and the division site regulating MinCDE proteins.
- Depth and depth–color coding using shape-adaptive wavelets38
A novel rate-constrained edge detection algorithm, which integrates the idea of significance bitplanes into the Canny edge detector, which provides an efficient way to extract and encode edges.
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- Characterizing Fatty Liver in vivo in Rabbits, Using Quantitative Ultrasound34
It is suggested that attenuation and BSC analysis can differentiate low versus high fat livers in a rabbit model of fatty liver disease and statistically significant differences are provided between low and high lipid fat classes.
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- SHREC'18: RGB-D object-to-CAD retrieval18
Evaluation results show that while the RGB-D to CAD retrieval problem is indeed challenging due to incomplete RGB-D reconstructions, it can be addressed to a certain extent using deep learning techniques trained on multi-view 2D images or 3D point clouds.
- RGB-D Object-to-CAD Retrieval18
Evaluation results show that while the RGB-D to CAD retrieval problem is indeed challenging due to incomplete RGB-D reconstructions, it can be addressed to a certain extent using deep learning techniques trained on multi-view 2D images or 3D point clouds.
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- 2D Scene Sketch-Based 3D Scene Retrieval14
The objective of this track is to evaluate the performance of different 2D scene sketch-based 3D scene retrieval algorithms using a 2D sketch query dataset and a 3D Warehouse model dataset and suggest several future research directions to tackle this research problem.
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- A comparison of methods for 3D scene shape retrieval11
A comprehensive comparison of all the above methods and an additional new retrieval methods are performed by evaluating them on the two benchmarks to solicit state-of-the-art approaches.
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- Feature-less Stitching of Cylindrical Tunnel7
This work utilizing known scene geometry along with recorded camera trajectory to create cylindrical images captured in a given environment such as a tunnel where the camera rotates around its center to create an immersive environment for end users.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-13. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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