Adapting Neural Networks at Runtime: Current Trends in At-Runtime Optimizations for Deep Learning
Adaptive optimization methods for deep learning adjust the inference task to the current
circumstances at runtime to improve the resource footprint while maintaining the model's …
circumstances at runtime to improve the resource footprint while maintaining the model's …
Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques
Video, as a key driver in the global explosion of digital information, can create tremendous
benefits for human society. Governments and enterprises are deploying innumerable …
benefits for human society. Governments and enterprises are deploying innumerable …
A systematic survey on recent deep learning-based approaches to multi-object tracking
H Agrawal, A Halder, P Chattopadhyay - Multimedia Tools and …, 2024 - Springer
This survey covers an in-depth review of the state-of-the-art research on Multi-Object
Tracking (MOT) from research articles published in 2019 or later in top-tier journals and …
Tracking (MOT) from research articles published in 2019 or later in top-tier journals and …
Learning Online Policies for Person Tracking in Multi-View Environments
In this paper, we introduce MVSparse, a novel and efficient framework for cooperative multi-
person tracking across multiple synchronized cameras. The MVSparse system is comprised …
person tracking across multiple synchronized cameras. The MVSparse system is comprised …