Zobrazeno 1 - 10
of 1 350
pro vyhledávání: '"P. Jayasuriya"'
Inverse Synthetic Aperture Radar (ISAR) imaging presents a formidable challenge when it comes to small everyday objects due to their limited Radar Cross-Section (RCS) and the inherent resolution constraints of radar systems. Existing ISAR reconstruct
Externí odkaz:
http://arxiv.org/abs/2410.10085
Autor:
Darabi, Nastaran, Jayasuriya, Dinithi, Naik, Devashri, Tulabandhula, Theja, Trivedi, Amit Ranjan
Adversarial attacks exploit vulnerabilities in a model's decision boundaries through small, carefully crafted perturbations that lead to significant mispredictions. In 3D vision, the high dimensionality and sparsity of data greatly expand the attack
Externí odkaz:
http://arxiv.org/abs/2409.12379
Publikováno v:
Optics Express 30, 40854-40870 (2022)
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, known as image dancing, is commonly characterized by its refractive-i
Externí odkaz:
http://arxiv.org/abs/2408.16623
Tackling image degradation due to atmospheric turbulence, particularly in dynamic environment, remains a challenge for long-range imaging systems. Existing techniques have been primarily designed for static scenes or scenes with small motion. This pa
Externí odkaz:
http://arxiv.org/abs/2404.13605
The study of non-line-of-sight (NLOS) imaging is growing due to its many potential applications, including rescue operations and pedestrian detection by self-driving cars. However, implementing NLOS imaging on a moving camera remains an open area of
Externí odkaz:
http://arxiv.org/abs/2404.05024
Autor:
Qu, Ziyuan, Vengurlekar, Omkar, Qadri, Mohamad, Zhang, Kevin, Kaess, Michael, Metzler, Christopher, Jayasuriya, Suren, Pediredla, Adithya
Differentiable 3D-Gaussian splatting (GS) is emerging as a prominent technique in computer vision and graphics for reconstructing 3D scenes. GS represents a scene as a set of 3D Gaussians with varying opacities and employs a computationally efficient
Externí odkaz:
http://arxiv.org/abs/2404.04687
Autor:
Darabi, Nastaran, Shukla, Priyesh, Jayasuriya, Dinithi, Kumar, Divake, Stutts, Alex C., Trivedi, Amit Ranjan
This paper addresses the challenging problem of energy-efficient and uncertainty-aware pose estimation in insect-scale drones, which is crucial for tasks such as surveillance in constricted spaces and for enabling non-intrusive spatial intelligence i
Externí odkaz:
http://arxiv.org/abs/2401.17481
Future food security is a major concern of the 21st century with the growing global population and climate changes. In addressing these challenges, protected cropping ensures food production year-round and increases crop production per land area by c
Externí odkaz:
http://arxiv.org/abs/2401.13928
Moving object segmentation in the presence of atmospheric turbulence is highly challenging due to turbulence-induced irregular and time-varying distortions. In this paper, we present an unsupervised approach for segmenting moving objects in videos do
Externí odkaz:
http://arxiv.org/abs/2311.03572
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 the concept of repeatability from measurement theory to describe this pr
Externí odkaz:
http://arxiv.org/abs/2310.17049