4 citations · 8 across the 5 of their papers we have counts for
5 papers
QD-BEV : Quantization-aware View-guided Distillation for Multi-view 3D Object Detection
Yifan Zhang, Zhen Dong, Huanrui Yang +6
Multi-view 3D detection based on BEV (bird-eye-view) has recently achieved significant improvements. However, the huge memory consumption of state-of-the-art models makes it hard t…
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…
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…
An Analog Neural Network Computing Engine using CMOS-Compatible Charge-Trap-Transistor (CTT)
Yuan Du, Li Du, Xuefeng Gu +8
An analog neural network computing engine based on CMOS-compatible charge-trap transistor (CTT) is proposed in this paper. CTT devices are used as analog multipliers. Compared to d…
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…