Geng Yang
Geng is a Ph.D student in the School of Communication Engineering at Xidian University in China,
supervised with Prof. Yunsong Li and Prof. Jie Lei.
She expects to graduate in Dec. 2024.
Her research focuses on algorithm-hardware co-design for DNN architecture and high-performance FPGA-based hardware acceleration.
Over the past three years, she has been dedicated to the development of an end-to-end DNN model inference acceleration system that integrates hardware-friendly model pruning and quantization, and FPGA-based hardware architecture.
She has actively participated in one National Natural Science Foundation of China and two large national projects under related topics. Geng’s work has been published in high-impact journals and references such as TRETS, TGRS, JSTAR, FPL, etc.
In recent months, she has been collaborating with Professor Zhenman Fang from Simon Fraser University on the hardware acceleration of larger and more complex DNN-Stable Diffsion inference.
Geng's Email: gengyang [at] stu.xidian.edu.cn
Email  / 
CV  / 
Google Scholar
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Research Interests
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SDA: Low-Bit Stable Diffusion Acceleration on Edge FPGAs
G. Yang, Y. Xie, Z. Xue, S. Chang, Y. Li, P. Dong, J. Lei, W. Xie, Y. Wang, X. Lin, Z. Fang
[FPL2024(Acceptance Rate: 22.8%, 29 out of 127)]
Paper/
Code
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SA4: A Comprehensive Analysis and Optimization of Systolic Array Architecture for 4-bit Convolutions
G. Yang, J. Lei, Z. Fang, J.Q. Zhang, J.R. Zhang, W. Xie,Y. Li
[FPL2024(Acceptance Rate: 22.8%, 29 out of 127)]
Paper/
Code
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Multimodal Informative ViT: Information Aggregation and Distribution for Hyperspectral and LiDAR Classification
J. Zhang, J. Lei, W. Xie, G. Yang, Y. Li
[TCSVT 2024]
Paper
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HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks
G. Yang, J. Lei, Z. Fang, Y. Li, J. Wang, W. Xie
[TRETS 2023]
[FPT 2023 Journal Track]
Paper/
FPT 2023 Oral report
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Guided Hybrid Quantization for Object Detection in Remote Sensing Imagery via One-to-one Self-teaching
J. Zhang, J. Lei, W. Xie, Y. Li, G. Yang, X. Jia
[TGRS 2023]
Paper
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Algorithm/hardware Codesign for Real-time On-satellite CNN-based Ship Detection in SAR Imagery
G. Yang, J. Lei, W. Xie, Z. Fang, Y. Li, J. Wang, X. Zhang
[TGRS 2022]
Paper/
Code
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A Low-complexity Hyperspectral Anomaly Detection Algorithm and its FPGA Implementation
J. Lei, G. Yang, W. Xie, Y. Li, X. Jia
[JSTAR 2022]
Paper /
Code /
Excellent Oral report in the 6th National Imaging Spectroscopic Earth Observation Symposium
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Rank-Aware Generative Adversarial Network for Hyperspectral Band Selection
X. Zhang, W. Xie, Y. Li, J. Lei, Q, Du, G. Yang
[TGRS 2022]
Paper
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Conference Abstracts
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E4SA: An Ultra-Efficient Systolic Array Architecture for 4-Bit Convolutional Neural Networks,
G. Yang, J. Lei, Z. Fang, J. Zhang, J. R. Zhang, W. Xie, Y. Li (FPGA 2024 poster)
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HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks,
G. Yang, J. Lei, Z. Fang, Y. Li, J. Wang, W. Xie (FCCM 2023 poster)
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Patents
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Object Detection Based on Feature Fusion with Masked Networks for SAR Imagery, J. Lei, Y. Guo, G. Yang, W. Xie, Y. Li.
(CN202211567684.4 on Octoer 8, 2022)
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Object Detection Joint Pruning and Quantization for SAR Imagery, J. Lei, J. Wang, G. Yang, W. Xie, Y. Li.
(CN202111488427.7 on December 8, 2021)
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FPGA-based Hyperspectral Anomaly Detection System, 2021, J. Lei, G. Yang, M. Zhang, W. Xie, Y. Li, T. Jiang, K. Liu, L. Gao.
(CN202110484719.7 on April 30, 2021)
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