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A. Dua, Li, Y. I. , and Ren, F. , Systolic-CNN: An OpenCL-defined Scalable Run-time-flexible FPGA Accelerator Architecture for Accelerating Convolutional Neural Network Inference in Cloud/Edge Computing, 2020.
Z. Liu, Li, Y. I. , Ren, F. , Yu, H. , and Goh, W. , SqueezedText: A Real-time Scene Text Recognition by Binary Convolutional Encoder-decoder Network, The AAAI Conference on Artificial Intelligence (AAAI). New Orleans, Louisana, pp. 7194-7201, 2018. (1.49 MB)
Z. Liu, Li, Y. I. , Ren, F. , Yu, H. , and Goh, W. , SqueezedText: A Real-time Scene Text Recognition by Binary Convolutional Encoder-decoder Network, The AAAI Conference on Artificial Intelligence (AAAI). New Orleans, Louisana, pp. 7194-7201, 2018. (1.49 MB)
F. Ren, Zhang, C. , Liu, L. , Xu, W. , Owall, V. , and Marković, D. , A Square-Root-Free Matrix Decomposition Method for Energy-Efficient Least Square Computation on Embedded Systems, IEEE Embedded Systems Letters, vol. 6, no. 4, pp. 73–76, 2014. (912.74 KB)
J. Ouyang, Lin, S. , Qi, W. , Wang, Y. , Yu, B. , and Jiang, S. , SDA: Software-defined accelerator for large-scale DNN systems, Hot Chips 26 Symposium (HCS), 2014 IEEE. IEEE, pp. 1–23, 2014.
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Y. Wei, Zhou, J. , Wang, Y. , Liu, Y. , Liu, Q. , Luo, J. , Wang, C. , Ren, F. , and Huang, L. , A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications, IEEE Transactions on Biomedical Circuits and Systems , vol. 14, no. 2, pp. 145-163, 2020. (2.08 MB)
Y. Wei, Zhou, J. , Wang, Y. , Liu, Y. , Liu, Q. , Luo, J. , Wang, C. , Ren, F. , and Huang, L. , A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications, IEEE Transactions on Biomedical Circuits and Systems , vol. 14, no. 2, pp. 145-163, 2020. (2.08 MB)
Y. Wei, Zhou, J. , Wang, Y. , Liu, Y. , Liu, Q. , Luo, J. , Wang, C. , Ren, F. , and Huang, L. , A Review of Algorithm & Hardware Design for AI-Based Biomedical Applications, IEEE Transactions on Biomedical Circuits and Systems , vol. 14, no. 2, pp. 145-163, 2020. (2.08 MB)
K. Kulkarni, Lohit, S. , Turaga, P. , Kerviche, R. , and Ashok, A. , Reconnet: Non-iterative reconstruction of images from compressively sensed measurements, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. pp. 449–458, 2016.
W. Li, Zhou, B. , Hsu, C. - Y. , Li, Y. I. , and Ren, F. , Recognizing terrain features on terrestrial surface using a deep learning model - An example with crater detection, 1st ACM SIGSPATIAL Workshop on Articial Intelligence and Deep Learning for Geographic Knowledge Discovery. ACM, Los Angeles, CA, pp. 33-36, 2017. (4.93 MB)
W. Li, Zhou, B. , Hsu, C. - Y. , Li, Y. I. , and Ren, F. , Recognizing terrain features on terrestrial surface using a deep learning model - An example with crater detection, 1st ACM SIGSPATIAL Workshop on Articial Intelligence and Deep Learning for Geographic Knowledge Discovery. ACM, Los Angeles, CA, pp. 33-36, 2017. (4.93 MB)
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M. Zinkevich, Weimer, M. , Li, L. , and Smola, A. J. , Parallelized stochastic gradient descent, Advances in neural information processing systems. pp. 2595–2603, 2010.
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C. Zhang, Li, P. , Sun, G. , Guan, Y. , Xiao, B. , and Cong, J. , Optimizing fpga-based accelerator design for deep convolutional neural networks, Proceedings of the 2015 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, pp. 161–170, 2015.
Y. Wang, Li, X. , Yu, H. , Ni, L. , Yang, W. , Weng, C. , and Zhao, J. , Optimizing boolean embedding matrix for compressive sensing in rram crossbar, Low Power Electronics and Design (ISLPED), 2015 IEEE/ACM International Symposium on. IEEE, pp. 13–18, 2015.
J. Zhao, Westerham, M. , Lakatos-Toth, M. , Zhang, Z. , Moskoff, A. , and Ren, F. , OpenICS: Open Image Compressive Sensing Toolbox and Benchmark, Software Impacts, vol. 9, 2021. (362.26 KB)
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X. Zhou, Peng, Y. , Long, C. , Ren, F. , and Shi, C. , MoNet3D: Towards Accurate Monocular 3D Object Localization in Real Time, The Thirty-seventh International Conference on Machine Learning. Virtual Event, 2020. (9.74 MB)
W. Xu, Huang, M. - C. , Liu, J. J. , Ren, F. , Shen, X. , Liu, X. , and Sarrafzadeh, M. , mCOPD: Mobile Phone Based Lung Function Diagnosis and Exercise System for COPD, Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA). ACM, 2013. (646.4 KB)
W. Xu, Huang, M. - C. , Liu, J. J. , Ren, F. , Shen, X. , Liu, X. , and Sarrafzadeh, M. , mCOPD: Mobile Phone Based Lung Function Diagnosis and Exercise System for COPD, Proceedings of the 6th International Conference on Pervasive Technologies Related to Assistive Environments (PETRA). ACM, 2013. (646.4 KB)
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Y. I. Li, Dua, A. , and Ren, F. , Light-Weight RetinaNet for Object Detection on Edge Devices, The 2020 IEEE World Forum on Internet of Things (WF-IoT'20). New Orleans, Louisiana, 2020. (2.43 MB)
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J. Li, Liang, J. , Li, L. , Ren, F. , Hu, W. , Li, J. , Qi, S. , and Pei, Q. , Healable Capacitive Touch Screen Sensors Based on Transparent Composite Electrodes Comprising Silver Nanowires and a Furan/Maleimide Diels-Alder Cycloaddition Polymer, ACS Nano, vol. 8, no. 12, pp. 12874–12882, 2014. (6.99 MB)
J. Li, Liang, J. , Li, L. , Ren, F. , Hu, W. , Li, J. , Qi, S. , and Pei, Q. , Healable Capacitive Touch Screen Sensors Based on Transparent Composite Electrodes Comprising Silver Nanowires and a Furan/Maleimide Diels-Alder Cycloaddition Polymer, ACS Nano, vol. 8, no. 12, pp. 12874–12882, 2014. (6.99 MB)
J. Li, Liang, J. , Li, L. , Ren, F. , Hu, W. , Li, J. , Qi, S. , and Pei, Q. , Healable Capacitive Touch Screen Sensors Based on Transparent Composite Electrodes Comprising Silver Nanowires and a Furan/Maleimide Diels-Alder Cycloaddition Polymer, ACS Nano, vol. 8, no. 12, pp. 12874–12882, 2014. (6.99 MB)
J. Li, Liang, J. , Li, L. , Ren, F. , Hu, W. , Li, J. , Qi, S. , and Pei, Q. , Healable Capacitive Touch Screen Sensors Based on Transparent Composite Electrodes Comprising Silver Nanowires and a Furan/Maleimide Diels-Alder Cycloaddition Polymer, ACS Nano, vol. 8, no. 12, pp. 12874–12882, 2014. (6.99 MB)
Y. I. Li, Hardware-friendly Deep Learning for Edge Computing, Arizona State University, Tempe, 2021. (7.78 MB)
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Y. I. Li, Liu, Z. , Xu, K. , Yu, H. , and Ren, F. , A GPU-Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks, ACM Journal on Emerging Technologies in Computing (JETC) - Special Issue on Frontiers of Hardware and Algorithms for On-chip Learning​, vol. 14, no. 2, p. 18.16, 2018. (1.92 MB)
Y. I. Li, Liu, Z. , Xu, K. , Yu, H. , and Ren, F. , A GPU-Outperforming FPGA Accelerator Architecture for Binary Convolutional Neural Networks, ACM Journal on Emerging Technologies in Computing (JETC) - Special Issue on Frontiers of Hardware and Algorithms for On-chip Learning​, vol. 14, no. 2, p. 18.16, 2018. (1.92 MB)
C. Szegedy, Liu, W. , Jia, Y. , Sermanet, P. , Reed, S. , Anguelov, D. , Erhan, D. , Vanhoucke, V. , and Rabinovich, A. , Going deeper with convolutions, Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 1–9, 2015.
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K. Xu, Li, Y. I. , and Ren, F. , An Energy-Efficient Compressive Sensing Framework Incorporating Online Dictionary Learning for Long-Term Wireless Health Monitoring, Proceedings of the 41st IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, Shanghai, China, pp. 804 - 808, 2016. (794.86 KB)
B. Li and Ren, F. , Enabling Deep Learning for Edge Computing. 2019. (5.52 MB)
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L. I. S. A. lab, Deep Learning Tutorial.. University of Montreal, 2015.
Y. LeCun, Bengio, Y. , and Hinton, G. , Deep learning, Nature, vol. 521, pp. 436–444, 2015.
Y. Wang, Li, X. , Xu, K. , Ren, F. , and Yu, H. , Data-Driven Sampling Matrix Boolean Optimization for Energy-Efficient Biomedical Signal Acquisition by Compressive Sensing, IEEE Transactions on Biomedical Circuits and Systems, vol. 11, no. 2, pp. 255-266, 2017. (2.53 MB)
K. Xu, Li, Y. , and Ren, F. , A Data-Driven Compressive Sensing Framework Tailored For Energy-Efficient Wearable Sensing, The 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). New Orleans, LA, pp. 861-865, 2017. (837.1 KB)
Y. Chen, Luo, T. , Liu, S. , Zhang, S. , He, L. , Wang, J. , Li, L. , Chen, T. , Xu, Z. , Sun, N. , and , , Dadiannao: A machine-learning supercomputer, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, pp. 609–622, 2014.
Y. Chen, Luo, T. , Liu, S. , Zhang, S. , He, L. , Wang, J. , Li, L. , Chen, T. , Xu, Z. , Sun, N. , and , , Dadiannao: A machine-learning supercomputer, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, pp. 609–622, 2014.
Y. Chen, Luo, T. , Liu, S. , Zhang, S. , He, L. , Wang, J. , Li, L. , Chen, T. , Xu, Z. , Sun, N. , and , , Dadiannao: A machine-learning supercomputer, Proceedings of the 47th Annual IEEE/ACM International Symposium on Microarchitecture. IEEE Computer Society, pp. 609–622, 2014.
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S. Qaisar, Bilal, R. Muhammad, Iqbal, W. , Naureen, M. , and Lee, S. , Compressive sensing: From theory to applications, a survey, Journal of Communications and networks, vol. 15, pp. 443–456, 2013.
Y. Shen, Zhu, G. , Li, J. , and Zhu, Z. , Compressed Sensing Image Reconstruction Algorithm by Dictionary Learning, Proceedings of International Conference on Internet Multimedia Computing and Service. ACM, p. 193, 2014.
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Y. I. Li, Zhang, S. , Zhou, X. , and Ren, F. , Build a Compact Binary Neural Network through Bit-level Sensitivity and Data Pruning, Neurocomputing, vol. 398, pp. 45-54, 2020. (1.91 MB)
Y. I. Li and Ren, F. , BNN Pruning: Pruning Binary Neural Network Guided by Weight Flipping Frequency, International Symposium on Quality Electronic Design (ISQED). Santa Clara, CA, 2020. (186.31 KB)
Z. Liu, Li, Y. , Ren, F. , and Yu, H. , A Binary Convolutional Encoder-decoder Network for Real-time Natural Scene Text Processing, The 1st International Workshop on Efficient Methods for Deep Neural Networks - Conference on Neural Information Processing Systems (NIPS). 2016. (773.3 KB)
Z. Liu, Li, Y. , Ren, F. , and Yu, H. , A Binary Convolutional Encoder-decoder Network for Real-time Natural Scene Text Processing, The 1st International Workshop on Efficient Methods for Deep Neural Networks - Conference on Neural Information Processing Systems (NIPS). 2016. (773.3 KB)
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Y. I. Li, Liu, Z. , Liu, W. , Jiang, Y. , Wang, Y. , Goh, W. Ling, Yu, H. , and Ren, F. , A 34-FPS 698-GOP/s/W Binarized Deep Neural Network-based Natural Scene Text Interpretation Accelerator for Mobile Edge Computing, IEEE Transactions on Industrial Electronics (TIE), vol. 66, no. 9, pp. 7407-7416, 2019. (3.34 MB)
Y. I. Li, Liu, Z. , Liu, W. , Jiang, Y. , Wang, Y. , Goh, W. Ling, Yu, H. , and Ren, F. , A 34-FPS 698-GOP/s/W Binarized Deep Neural Network-based Natural Scene Text Interpretation Accelerator for Mobile Edge Computing, IEEE Transactions on Industrial Electronics (TIE), vol. 66, no. 9, pp. 7407-7416, 2019. (3.34 MB)
Y. I. Li, Liu, Z. , Liu, W. , Jiang, Y. , Wang, Y. , Goh, W. Ling, Yu, H. , and Ren, F. , A 34-FPS 698-GOP/s/W Binarized Deep Neural Network-based Natural Scene Text Interpretation Accelerator for Mobile Edge Computing, IEEE Transactions on Industrial Electronics (TIE), vol. 66, no. 9, pp. 7407-7416, 2019. (3.34 MB)