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pro vyhledávání: '"Singh, Rajhans"'
Autor:
Sornapudi, Sudhir, Singh, Rajhans
Computer vision in agriculture is game-changing with its ability to transform farming into a data-driven, precise, and sustainable industry. Deep learning has empowered agriculture vision to analyze vast, complex visual data, but heavily rely on the
Externí odkaz:
http://arxiv.org/abs/2403.15248
Implicit neural representations (INR) have gained significant popularity for signal and image representation for many end-tasks, such as superresolution, 3D modeling, and more. Most INR architectures rely on sinusoidal positional encoding, which acco
Externí odkaz:
http://arxiv.org/abs/2303.11424
Deep networks for image classification often rely more on texture information than object shape. While efforts have been made to make deep-models shape-aware, it is often difficult to make such models simple, interpretable, or rooted in known mathema
Externí odkaz:
http://arxiv.org/abs/2205.11722
Recently, there has been substantial progress in image synthesis from semantic labelmaps. However, methods used for this task assume the availability of complete and unambiguous labelmaps, with instance boundaries of objects, and class labels for eac
Externí odkaz:
http://arxiv.org/abs/2004.08614
Publikováno v:
International Conference on Machine Learning (2019)
The advent of generative adversarial networks (GAN) has enabled new capabilities in synthesis, interpolation, and data augmentation heretofore considered very challenging. However, one of the common assumptions in most GAN architectures is the assump
Externí odkaz:
http://arxiv.org/abs/1905.07061
In resource-constrained environments, one can employ spatial multiplexing cameras to acquire a small number of measurements of a scene, and perform effective reconstruction or high-level inference using purely data-driven neural networks. However, on
Externí odkaz:
http://arxiv.org/abs/1809.02850
Autor:
Shukla, Ankita, Dadhich, Rishi, Singh, Rajhans, Rayas, Anirudh, Saidi, Pouria, Dasarathy, Gautam, Berisha, Visar, Turaga, Pavan
Publikováno v:
Frontiers in Computer Science; 2024, p1-11, 11p
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