A survey of model compression strategies for object detection

Z Lyu, T Yu, F Pan, Y Zhang, J Luo, D Zhang… - Multimedia tools and …, 2024 - Springer
Deep neural networks (DNNs) have achieved great success in many object detection tasks.
However, such DNNS-based large object detection models are generally computationally …

Image recognition based on lightweight convolutional neural network: Recent advances

Y Liu, J Xue, D Li, W Zhang, TK Chiew, Z Xu - Image and Vision Computing, 2024 - Elsevier
Image recognition is an important task in computer vision with broad applications. In recent
years, with the advent of deep learning, lightweight convolutional neural network (CNN) has …

Pruning parameterization with bi-level optimization for efficient semantic segmentation on the edge

C Yang, P Zhao, Y Li, W Niu, J Guan… - Proceedings of the …, 2023 - openaccess.thecvf.com
With the ever-increasing popularity of edge devices, it is necessary to implement real-time
segmentation on the edge for autonomous driving and many other applications. Vision …

HALOC: hardware-aware automatic low-rank compression for compact neural networks

J **ao, C Zhang, Y Gong, M Yin, Y Sui… - Proceedings of the …, 2023 - ojs.aaai.org
Low-rank compression is an important model compression strategy for obtaining compact
neural network models. In general, because the rank values directly determine the model …