Song Han
Massachusetts Institute of Technology
Assistant Professor
Department of Electrical Engineering and Computer Science
Research Area
#Computer science#Artificial intelligence#Artificial neural network#Computer engineering#Deep learning#Field-programmable gate array#Inference#Computer hardware#Convolutional neural network#Speedup
SCIE paper information
Papers relevant to ‘Computer science’: 10
Research performance of SCIE papers matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA
2018/01 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2.402 Impact Factor 246 citations
Software-Hardware Codesign for Efficient Neural Network Acceleration
2017/03 IEEE MICRO 1.913 Impact Factor 50 citations
Papers for author ‘Song Han’: 11
Number of published SCIE papers by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Angel-Eye: A Complete Design Flow for Mapping CNN Onto Embedded FPGA
2018/01 IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2.402 Impact Factor 246 citations
Fast inference of deep neural networks in FPGAs for particle physics
2018/04 JOURNAL OF INSTRUMENTATION 1.366 Impact Factor 133 citations
conference information
Papers relevant to ‘Computer science’: 25
Research performance of Top-tier Conference matching with ‘Computer science’
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Learning both weights and connections for efficient neural networks
2015/12 NEURIPS Top-tier Conference 3209 citations
EIE: efficient inference engine on compressed deep neural network
2016/06 ISCA Top-tier Conference 1665 citations
Papers for author ‘Song Han’: 25
Number of published Top-tier Conference by year
*Papers published between 2014 and 2020 were selected, and the citation number was determined by bing.com.
Learning both weights and connections for efficient neural networks
2015/12 NEURIPS Top-tier Conference 3209 citations
EIE: efficient inference engine on compressed deep neural network
2016/06 ISCA Top-tier Conference 1665 citations
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