no code implementations • 20 Oct 2024 • Shirong Zheng, Shaobo Liu, Zhenhong Zhang, Dian Gu, Chunqiu Xia, Huadong Pang, Enock Mintah Ampaw
The main contribution of this research is the development of a robust model that leverages the strengths of TRIZ and advanced deep learning techniques, improving the accuracy of energy consumption predictions.
no code implementations • 10 Jan 2022 • Jing Du, ShiLiang Pu, Qinbo Dong, Chao Jin, Xin Qi, Dian Gu, Ru Wu, Hongwei Zhou
Although modern automatic speech recognition (ASR) systems can achieve high performance, they may produce errors that weaken readers' experience and do harm to downstream tasks.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 18 Nov 2019 • Ke He, Bo Liu, Yu Zhang, Andrew Ling, Dian Gu
In this paper, we firstly propose the FeCaffe, i. e. FPGA-enabled Caffe, a hierarchical software and hardware design methodology based on the Caffe to enable FPGA to support mainline deep learning development features, e. g. training and inference with Caffe.