Mobile and Intelligent Computing Laboratory
Publications

Publications

Logo-CV

Conference

[ISLPED’20] Enabling Efficient ReRAM-based Neural Network Computing via Crossbar Structure Adaptive Optimization.
C. Liu, F. Yu, Z. Qin, and X. Chen.
The  ACM/IEEE International Symposium on Low Power Electronics and Design, Aug. 2020.

[DATE’20] DCCNN: Computational Flow Redefinition for Efficient CNN Inference through Model Structural Decoupling.
F. Yu, Z. Qin, D. Wang, P. Xu, C. Liu, T. Zhi, and X. Chen.
The 23rd Design, Automation and Test in Europe Conference, Mar. 2020.

[SEC’19] Task-Adaptive Incremental Learning for Intelligent Edge Devices.
Z. Qin, F. Yu, and X. Chen.
The 4th ACM/IEEE Symposium on Edge Computing,Nov. 2019.

[IJCAI’19] Interpreting and Evaluating Neural Network Robustness.
F. Yu, Z. Qin, C. Liu, and X. Chen.
The 28th International Joint Conference on Artificial Intelligence, Aug. 2019.

[BMVC’19] Functionality-Oriented Convolutional Filter Pruning.
Z. Qin, F. Yu, C. Liu, and X. Chen.
The the 30th British Machine Vision Conference, Sep. 2019.

[ASPDAC’19] CAPTOR: A Class Adaptive Filter Pruning Framework for Convolutional Neural Networks in Mobile Applications.
Z. Qin, F. Yu, C. Liu, and X. Chen.
The 24th Asia and South Pacific Design Automation Conference, pp. 444~449, Jan. 2019.

[NeurIPS Workshop’18] Demystifying Neural Network Filter Pruning.
The 24th Asia and South Pacific Design Automation Conference, pp. 444~449, Jan. 2019.
The 32nd Conference on Neural Information Processing Systems, Workshop on Compact Deep Neural Network Representation with Industrial Applications, Dec. 2018.

[NeurIPS Workshop’18] Distilling Critical Paths in Convolutional Neural Networks.
F. Yu, Z. Qin, C. Liu, and X. Chen.
The 32nd Conference on Neural Information Processing Systems, Workshop on Compact Deep Neural Network Representation with Industrial Applications, Dec. 2018.

[ISLPED’18] DiReCt: Resource-Aware Dynamic Model Reconfiguration for Convolutional Neural Network in Mobile Systems.
Z. Xu, Z. Qin, F. Yu, C. Liu, and X. Chen.
The 23rd International Symposium on Low Power Electronics and Design, No. 37, pp. 16, Jul. 2018.

[ICCAD’17] VoCaM: Visualization Oriented Convolutional Neural Network Acceleration on Mobile System.
Z. Qin, Z. Xu, Q. Dong, Y. Chen, and X. Chen.
The 36th International Conference on Computer-Aided Design, pp. 835~840, Nov. 2017.

[ICCAD’17] AdaLearner: An Adaptive Distributed Mobile Learning System for Neural Networks.
J. Mao, Z. Qin, Z. Xu, K. Nixon, X. Chen, H. Li, and Y. Chen.
The 36th International Conference on Computer-Aided Design, pp. 291~296, Nov. 2017.

Journal

[IEE-TCAD’21] CAPTORX: A Class-Adaptive Convolutional Neural Network Reconguration Framework for Ecient Distributed Mobile Computing.
Z. Qin, F. Yu, Z. Xu, C. Liu, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, to appear.

[IEE-TCAD’20] REIN the RobuTS: Robust DNN-based Image Recognition in Autonomous Driving Systems.
F. Yu, Z. Qin, C. Liu, W Di, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Oct, 2020.

[IEE-TCAD’20] DiReCtX: Dynamic Resource-Aware CNN Reconfiguration Framework for Real-Time Mobile Application.
Z. Xu, F. Yu, Z. Qin, C. Liu, and X. Chen.
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, May, 2020.

[AMC-MFC’18] How convolutional neural networks see the world – A survey of convolutional neural network visualization methods.
Z. Qin, F. Yu, C. Liu, and X. Chen.
Advances in Mathematics of Communications Journal on Mathematical Foundations of Computing, May, 2018.