Peining Zhen
Orcid: 0000-0002-8439-876X
According to our database1,
Peining Zhen
authored at least 15 papers
between 2019 and 2023.
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Bibliography
2023
A Highly Compressed Accelerator With Temporal Optical Flow Feature Fusion and Tensorized LSTM for Video Action Recognition on Terminal Device.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., October, 2023
A Deep Learning Framework for Solving Stress-based Partial Differential Equations in Electromigration Analysis.
ACM Trans. Design Autom. Electr. Syst., July, 2023
Toward Compact Transformers for End-to-End Object Detection With Decomposed Chain Tensor Structure.
IEEE Trans. Circuits Syst. Video Technol., February, 2023
Multilayer Perceptron-Based Stress Evolution Analysis Under DC Current Stressing for Multisegment Wires.
IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., February, 2023
Towards Accurate Oriented Object Detection in Aerial Images with Adaptive Multi-level Feature Fusion.
ACM Trans. Multim. Comput. Commun. Appl., January, 2023
2022
IEICE Trans. Inf. Syst., 2022
HFOD: A hardware-friendly quantization method for object detection on embedded FPGAs.
IEICE Electron. Express, 2022
Multilayer Perceptron Based Stress Evolution Analysis under DC Current Stressing for Multi-segment Wires.
CoRR, 2022
FASSST: Fast Attention Based Single-Stage Segmentation Net for Real-Time Instance Segmentation.
Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022
2021
Fast Video Facial Expression Recognition by a Deeply Tensor-Compressed LSTM Neural Network for Mobile Devices.
ACM Trans. Internet Things, 2021
2020
ABCD: A Compact Object Detector Based on Channel Quantization and Tensor Decomposition.
Proceedings of the 10th IEEE International Conference on Consumer Electronics, 2020
Proceedings of the 2020 Design, Automation & Test in Europe Conference & Exhibition, 2020
Proceedings of the 2020 IEEE Asia Pacific Conference on Circuits and Systems, 2020
2019
Fast video facial expression recognition by deeply tensor-compressed LSTM neural network on mobile device.
Proceedings of the 4th ACM/IEEE Symposium on Edge Computing, 2019