19 citations · 101 across the 25 of their papers we have counts for
14 papers · 1 filter
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,…
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…
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…
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,…
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…
Frequency Domain TOF: Encoding Object Depth in Modulation Frequency
Achuta Kadambi, Vage Taamazyan, Suren Jayasuriya +1
Time of flight cameras may emerge as the 3-D sensor of choice. Today, time of flight sensors use phase-based sampling, where the phase delay between emitted and received, high-freq…