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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)
X. Zhang, Xu, W. , Huang, M. - C. , Amini, N. , and Ren, F. , “See UV on Your Skin: An Ultraviolet Sensing and Visualization System”, Proceedings of the 8th International Conference on Body Area Networks (BodyNets). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), pp. 22-28, 2013. (1.82 MB)
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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)
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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X. Zhang, Huang, M. - C. , Ren, F. , Xu, W. , Guan, N. , and Yi, W. , “Proper Running Posture Guide: A Wearable Biomechanics Capture System”, Proceedings of the 8th International Conference on Body Area Networks (BodyNets). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), 2013. (1.54 MB)
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)
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)
M. Mehdi Ghahremanpour, Arab, S. Shahriar, Biookaghazadeh, S. , Zhang, J. , and van der Spoel, D. , “MemBuilder: a web-based graphical interface to build heterogeneously mixed membrane bilayers for the GROMACS biomolecular simulation program”, Bioinformatics, vol. 30, pp. 439–441, 2013. (192.44 KB)
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F. Ren, Xu, K. , and Zhang, Z. , “LAPRAN: A SCALABLE LAPLACIAN PYRAMID RECONSTRUCTIVE ADVERSARIAL NETWORK FOR FLEXIBLE COMPRESSIVE SENSING RECONSTRUCTION”, 16/745,817, 2020.
K. Xu, Zhang, Z. , and Ren, F. , “LAPRAN: A Scalable Laplacian Pyramid Reconstructive Adversarial Network for Flexible Compressive Sensing Reconstruction”, The 15th European Conference on Computer Vision (ECCV'18). Munich, Germany, pp. 491-507, 2018. (1.41 MB)
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S. Biookaghazadeh, “Kaleido: Enabling Efficient Scientific Data Processing on Big-Data Systems”, Networking, Architecture, and Storage (NAS), 2017 International Conference on. IEEE, pp. 1–10, 2017.
S. Biookaghazadeh, “Kaleido: Enabling Efficient Scientific Data Processing on Big-Data Systems”, Networking, Architecture, and Storage (NAS), 2017 International Conference on. IEEE, pp. 1–10, 2017.
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Z. Zhang, Zhao, J. , and Ren, F. , “An Experimental Study on Transferring Data-Driven Image Compressive Sensing to Bioelectric Signals”, The 47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Singapore, pp. 1191-1195, 2022. (1.29 MB)
Z. Zhang, Zhao, J. , and Ren, F. , “An Experimental Study on Transferring Data-Driven Image Compressive Sensing to Bioelectric Signals”, The 47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Singapore, pp. 1191-1195, 2022. (1.29 MB)
Z. Zhang, Yu, Z. , You, S. , Rao, R. , Agarwal, S. , and Ren, F. , “Enhanced Low-resolution LiDAR-Camera Calibration Via Depth Interpolation and Supervised Contrastive Learning”, The 48th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23). Rhodes Island, Greece, 2023. (2.95 MB)
S. Biookaghazadeh, Xu, Y. , Zhou, S. , and Zhao, M. , “Enabling scientific data storage and processing on big-data systems”, Big Data (Big Data), 2015 IEEE International Conference on. IEEE, pp. 1978–1984, 2015. (966.13 KB)
S. Biookaghazadeh, Xu, Y. , Zhou, S. , and Zhao, M. , “Enabling scientific data storage and processing on big-data systems”, Big Data (Big Data), 2015 IEEE International Conference on. IEEE, pp. 1978–1984, 2015. (966.13 KB)
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Y. Feng, Yang, F. , Zhou, X. , Guo, Y. , Tang, F. , Ren, F. , Guo, J. , and Ji, S. , “A Deep Learning Approach for Targeted Contrast-Enhanced Ultrasound Based Prostate Cancer Detection”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, vol. 16, no. 6, pp. 1794-1801, 2019. (1.73 MB)
Z. Yu, Trindade, B. Machado, Green, M. , Zhang, Z. , Sneha, P. , Bank-Tavakoli, E. , Pawlowicz, C. , and Ren, F. , “A Data-Driven Approach for Automated Integrated Circuit Segmentation of Scan Electron Microscopy Images”, The 29th IEEE International Conference on Image Processing (ICIP). Bordeaux, France, 2022. (1.03 MB)
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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Z. Zhang, Xu, K. , and Ren, F. , “CRA: A Generic Compression Ratio Adaptor for End-to-end Data-driven Image Compressive Sensing Reconstruction Frameworks”, International Conference on Acoustics, Speech, and Signal Processing. Barcelona, Spain, pp. 1740-1749, 2020. (328.74 KB)
H. Huang, Yu, H. , Zhuo, C. , and Ren, F. , “A Compressive-sensing based Testing Vehicle for 3D TSV Pre-bond and Post-bond Testing Data”, International Symposium on Physical Design (ISPD). pp. 19-25, 2016. (1.21 MB)
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.
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, 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)
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Z. Zhang, Trindade, B. Machado, Green, M. , Yu, Z. , Pawlowicz, C. , and Ren, F. , “Automatic Error Detection in Integrated Circuits Image Segmentation: A Data-driven Approach”, The 48th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'23). Rhodes Island, Greece, 2023. (501.02 KB)
S. Biookaghazadeh, Zhao, M. , and Ren, F. , “Are FPGAs Suitable for Edge Computing?”, The USENIX Workshop on Hot Topics in Edge Computing (HotEdge '18). BOSTON, MA, 2018. (363.22 KB)