19 citations · 101 across the 25 of their papers we have counts for
27 papers
Turbulence Strength Estimation from Video using Physics-based Deep Learning
Ripon Kumar Saha, Esen Salcin, Jihoo Kim +2
Images captured from a long distance suffer from dynamic image distortion due to turbulent flow of air cells with random temperatures, and thus refractive indices. This phenomenon,…
Learning Repeatable Speech Embeddings Using An Intra-class Correlation Regularizer
Jianwei Zhang, Suren Jayasuriya, Visar Berisha
A good supervised embedding for a specific machine learning task is only sensitive to changes in the label of interest and is invariant to other confounding factors. We leverage th…
Neural Volumetric Reconstruction for Coherent Synthetic Aperture Sonar
Albert W. Reed, Juhyeon Kim, Thomas Blanford +3
Synthetic aperture sonar (SAS) measures a scene from multiple views in order to increase the resolution of reconstructed imagery. Image reconstruction methods for SAS coherently co…
Eulerian Phase-based Motion Magnification for High-Fidelity Vital Sign Estimation with Radar in Clinical Settings
Md Farhan Tasnim Oshim, Toral Surti, Stephanie Carreiro +3
Efficient and accurate detection of subtle motion generated from small objects in noisy environments, as needed for vital sign monitoring, is challenging, but can be substantially…
Towards Live 3D Reconstruction from Wearable Video: An Evaluation of V-SLAM, NeRF, and Videogrammetry Techniques
David Ramirez, Suren Jayasuriya, Andreas Spanias
Mixed reality (MR) is a key technology which promises to change the future of warfare. An MR hybrid of physical outdoor environments and virtual military training will enable engag…
Robust Vocal Quality Feature Embeddings for Dysphonic Voice Detection
Jianwei Zhang, Julie Liss, Suren Jayasuriya +1
Approximately 1.2% of the world's population has impaired voice production. As a result, automatic dysphonic voice detection has attracted considerable academic and clinical intere…
SINR: Deconvolving Circular SAS Images Using Implicit Neural Representations
Albert Reed, Thomas Blanford, Daniel C. Brown +1
Circular Synthetic aperture sonars (CSAS) capture multiple observations of a scene to reconstruct high-resolution images. We can characterize resolution by modeling CSAS imaging as…
Adaptive Subsampling for ROI-based Visual Tracking: Algorithms and FPGA Implementation
Odrika Iqbal, Victor Isaac Torres Muro, Sameeksha Katoch +2
There is tremendous scope for improving the energy efficiency of embedded vision systems by incorporating programmable region-of-interest (ROI) readout in the image sensor design.…
Implicit Neural Representations for Deconvolving SAS Images
Albert Reed, Thomas Blanford, Daniel C. Brown +1
Synthetic aperture sonar (SAS) image resolution is constrained by waveform bandwidth and array geometry. Specifically, the waveform bandwidth determines a point spread function (PS…
Deep Camera Obscura: An Image Restoration Pipeline for Lensless Pinhole Photography
Joshua D. Rego, Huaijin Chen, Shuai Li +2
The lensless pinhole camera is perhaps the earliest and simplest form of an imaging system using only a pinhole-sized aperture in place of a lens. They can capture an infinite dept…
Dynamic CT Reconstruction from Limited Views with Implicit Neural Representations and Parametric Motion Fields
Albert W. Reed, Hyojin Kim, Rushil Anirudh +4
Reconstructing dynamic, time-varying scenes with computed tomography (4D-CT) is a challenging and ill-posed problem common to industrial and medical settings. Existing 4D-CT recons…
Restoring degraded speech via a modified diffusion model
Jianwei Zhang, Suren Jayasuriya, Visar Berisha
There are many deterministic mathematical operations (e.g. compression, clipping, downsampling) that degrade speech quality considerably. In this paper we introduce a neural networ…
Differentiable Programming for Hyperspectral Unmixing using a Physics-based Dispersion Model
John Janiczek, Parth Thaker, Gautam Dasarathy +3
Hyperspectral unmixing is an important remote sensing task with applications including material identification and analysis. Characteristic spectral features make many pure materia…
Thresholded Non-Uniform Fourier Frame-Based Reconstruction for Stripmap SAR
John McKay, Anne Gelb, Suren Jayasuriya +1
Fourier domain methods are fast algorithms for SAR imaging. They typically involve an interpolation in the frequency domain to re-grid non-uniform data so inverse fast Fourier tran…
Coupling Rendering and Generative Adversarial Networks for Artificial SAS Image Generation
Albert Reed, Isaac Gerg, John McKay +3
Acquisition of Synthetic Aperture Sonar (SAS) datasets is bottlenecked by the costly deployment of SAS imaging systems, and even when data acquisition is possible,the data is often…
Non-Parametric Priors For Generative Adversarial Networks
Rajhans Singh, Pavan Turaga, Suren Jayasuriya +2
The advent of generative adversarial networks (GAN) has enabled new capabilities in synthesis, interpolation, and data augmentation heretofore considered very challenging. However,…
Adaptive Lighting for Data-Driven Non-Line-of-Sight 3D Localization and Object Identification
Sreenithy Chandran, Suren Jayasuriya
Non-line-of-sight (NLOS) imaging of objects not visible to either the camera or illumination source is a challenging task with vital applications including surveillance and robotic…
CS-VQA: Visual Question Answering with Compressively Sensed Images
Li-Chi Huang, Kuldeep Kulkarni, Anik Jha +3
Visual Question Answering (VQA) is a complex semantic task requiring both natural language processing and visual recognition. In this paper, we explore whether VQA is solvable when…
EVA: Exploiting Temporal Redundancy in Live Computer Vision
Mark Buckler, Philip Bedoukian, Suren Jayasuriya +1
Hardware support for deep convolutional neural networks (CNNs) is critical to advanced computer vision in mobile and embedded devices. Current designs, however, accelerate generic…
Compressive Light Field Reconstructions using Deep Learning
Mayank Gupta, Arjun Jauhari, Kuldeep Kulkarni +3
Light field imaging is limited in its computational processing demands of high sampling for both spatial and angular dimensions. Single-shot light field cameras sacrifice spatial r…
Reconfiguring the Imaging Pipeline for Computer Vision
Mark Buckler, Suren Jayasuriya, Adrian Sampson
Advancements in deep learning have ignited an explosion of research on efficient hardware for embedded computer vision. Hardware vision acceleration, however, does not address the…
Deep Learning with Energy-efficient Binary Gradient Cameras
Suren Jayasuriya, Orazio Gallo, Jinwei Gu +1
Power consumption is a critical factor for the deployment of embedded computer vision systems. We explore the use of computational cameras that directly output binary gradient imag…
ASP Vision: Optically Computing the First Layer of Convolutional Neural Networks using Angle Sensitive Pixels
Huaijin Chen, Suren Jayasuriya, Jiyue Yang +4
Deep learning using convolutional neural networks (CNNs) is quickly becoming the state-of-the-art for challenging computer vision applications. However, deep learning's power consu…
Depth Fields: Extending Light Field Techniques to Time-of-Flight Imaging
Suren Jayasuriya, Adithya Pediredla, Sriram Sivaramakrishnan +2
A variety of techniques such as light field, structured illumination, and time-of-flight (TOF) are commonly used for depth acquisition in consumer imaging, robotics and many other…