1 citations · 1 across the 3 of their papers we have counts for
5 papers
Label-Guided Knowledge Distillation for 3D-CNNs in Action Recognition
Yanjiang Shi, Peng Zhao, Nan Qi +1
As a key model compression technique, knowledge distillation aims to transfer knowledge from a high-capacity teacher model to a lightweight student model for enhancing the latter's…
EdgeSync: Accelerating Edge-Model Updates for Data Drift through Adaptive Continuous Learning
Runchu Donga, Peng Zhao, Guiqin Wang +2
Real-time video analytics systems typically deploy lightweight models on edge devices to reduce latency. However, the distribution of data features may change over time due to vari…
Generative Model-Based Feature Attention Module for Video Action Analysis
Guiqin Wang, Peng Zhao, Cong Zhao +3
Video action analysis is a foundational technology within the realm of intelligent video comprehension, particularly concerning its application in Internet of Things(IoT). However,…
EdgeSync: Faster Edge-model Updating via Adaptive Continuous Learning for Video Data Drift
Peng Zhao, Runchu Dong, Guiqin Wang +1
Real-time video analytics systems typically place models with fewer weights on edge devices to reduce latency. The distribution of video content features may change over time for v…
CDC: Classification Driven Compression for Bandwidth Efficient Edge-Cloud Collaborative Deep Learning
Yuanrui Dong, Peng Zhao, Hanqiao Yu +2
The emerging edge-cloud collaborative Deep Learning (DL) paradigm aims at improving the performance of practical DL implementations in terms of cloud bandwidth consumption, respons…