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2022
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)
2019
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. 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)
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)
2018
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)
2015
S. Gupta, Agrawal, A. , Gopalakrishnan, K. , and Narayanan, P. , Deep learning with limited numerical precision, Proceedings of the 32nd International Conference on Machine Learning (ICML-15). pp. 1737–1746, 2015.
S. Gupta, Agrawal, A. , Gopalakrishnan, K. , and Narayanan, P. , Deep learning with limited numerical precision, Proceedings of the 32nd International Conference on Machine Learning (ICML-15). pp. 1737–1746, 2015.
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.
A. Putnam, Caulfield, A. M. , Chung, E. S. , Chiou, D. , Constantinides, K. , Demme, J. , Esmaeilzadeh, H. , Fowers, J. , Gopal, G. Prashanth, Gray, J. , and , , A reconfigurable fabric for accelerating large-scale datacenter services, IEEE Micro, vol. 35, pp. 10–22, 2015.
A. Putnam, Caulfield, A. M. , Chung, E. S. , Chiou, D. , Constantinides, K. , Demme, J. , Esmaeilzadeh, H. , Fowers, J. , Gopal, G. Prashanth, Gray, J. , and , , A reconfigurable fabric for accelerating large-scale datacenter services, IEEE Micro, vol. 35, pp. 10–22, 2015.
2014
L. Cheng, Xu, W. , Ren, F. , Gong, F. , Gupta, P. , and He, L. , Statistical Timing and Power Analysis of VLSI Considering Non-linear Dependence, the VLSI Journal Integration, vol. 47, no. 4, pp. 487–498, 2014. (845.26 KB)
L. Cheng, Xu, W. , Ren, F. , Gong, F. , Gupta, P. , and He, L. , Statistical Timing and Power Analysis of VLSI Considering Non-linear Dependence, the VLSI Journal Integration, vol. 47, no. 4, pp. 487–498, 2014. (845.26 KB)
2013
S. Nam, Davies, M. E. , Elad, M. , and Gribonval, R. , The cosparse analysis model and algorithms, Applied and Computational Harmonic Analysis, vol. 34, pp. 30–56, 2013.
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)
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)
2009
B. Pérez-Sánchez, Fontenla-Romero, O. , and Guijarro-Berdiñas, B. , A supervised learning method for neural networks based on sensitivity analysis with automatic regularization, International Work-Conference on Artificial Neural Networks. Springer, pp. 157–164, 2009.
2007
J. A. Tropp and Gilbert, A. C. , Signal recovery from random measurements via orthogonal matching pursuit, IEEE Transactions on information theory, vol. 53, pp. 4655–4666, 2007.