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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
ReMatch+ Intern - Sarah Kuo duration 3 minutes 6 seconds ReMatch+ Intern - Sarah Kuo ReMatch+ Intern - Sarah Kuo	ReMatch+ Intern - Sarah Kuo Electrotaxis in C. elegans movement field behavior neurons angle elegans lab tracker worms strength pattern response brain interactions c. increase angles systems tracking fields From our Undergraduate Research 1 likes 46 plays Date July 27th, 2021 Speaker Sarah Kuo Department Department of Physics
Reserve Requests: Add/Edit/Delete Items duration 3 minutes 27 seconds Reserve Requests: Add/Edit/Delete Items Reserve Requests: Add/Edit/Delete Items	Reserve Requests: Add/Edit/Delete Items reserves article week form requests title request tutorial laptop trackpad bottom note edit processing status history tracking workflow pdf url From PU Princeton University Library 0 likes 36 plays Date December 18th, 2020 Department Princeton University Library