4 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.AR2021
Memory-Efficient CNN Accelerator Based on Interlayer Feature Map Compression
Zhuang Shao, Xiaoliang Chen, Li Du +6
Existing deep convolutional neural networks (CNNs) generate massive interlayer feature data during network inference. To maintain real-time processing in embedded systems, large on…
cs.AR2017★ 4 cited
A Streaming Accelerator for Deep Convolutional Neural Networks with Image and Feature Decomposition for Resource-limited System Applications
Yuan Du, Li Du, Yilei Li +2
Deep convolutional neural networks (CNN) are widely used in modern artificial intelligence (AI) and smart vision systems but also limited by computation latency, throughput, and en…
cs.CV2017★ 1 cited
A Reconfigurable Streaming Deep Convolutional Neural Network Accelerator for Internet of Things
Li Du, Yuan Du, Yilei Li +1
Convolutional neural network (CNN) offers significant accuracy in image detection. To implement image detection using CNN in the internet of things (IoT) devices, a streaming hardw…