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Inverse Neural Rendering for Explainable… duration 3 minutes 0 seconds Inverse Neural Rendering for Explainable… Inverse Neural Rendering for Explainable Multi-Object Tracking, Tanushree Banerjee, UG '24 (611179F4)	Inverse Neural Rendering for Explainable Multi-Object Tracking, Tanushree Banerjee, UG '24 (611179F4) Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via fine-tuning, it… prd24 object properties image graphics cars tracking approach prediction appearance shape pipeline driving model feed features input frames problem approaches computer From Research Princeton Research Day 5 likes 379 plays Date May 3rd, 2024 Speaker Tanushree Banerjee, UG '24 (611179F4) Department Computer Science
Zhdankin, Vladimir, February 8, 2023… duration 28 minutes 37 seconds Zhdankin, Vladimir, February 8, 2023… Zhdankin, Vladimir, February 8, 2023 "Nonthermal Particle Acceleration by Turbulence and the Rayleigh-Taylor Instability"	Zhdankin, Vladimir, February 8, 2023 "Nonthermal Particle Acceleration by Turbulence and the Rayleigh-Taylor Instability" turbulence particle density reconnection field driving acceleration power regime particles lot plasma instability taylor energy law accretion rotation beta difference From Broadcast Broadcast Center Staff 0 likes 37 plays Date February 8th, 2023 Speaker Vladimir Zhdankin Department PCTS Location Jadwin

Inverse Neural Rendering for Explainable…

duration 3 minutes 0 seconds

Inverse Neural Rendering for Explainable…

Inverse Neural Rendering for Explainable Multi-Object Tracking, Tanushree Banerjee, UG '24 (611179F4)

Today, most methods for image understanding tasks rely on feed-forward neural networks. While this approach has allowed for empirical accuracy, efficiency, and task adaptation via fine-tuning, it…