| PipeCNN: An OpenCL-based open-source FPGA accelerator for convolution neural networks D Wang, K Xu, D Jiang 2017 International Conference on Field Programmable Technology (ICFPT), 279-282, 2017 | 96 | 2017 |
| Sparse-YOLO: Hardware/software co-design of an FPGA accelerator for YOLOv2 Z Wang, K Xu, S Wu, L Liu, L Liu, D Wang IEEE Access 8, 116569-116585, 2020 | 69 | 2020 |
| PipeCNN: An OpenCL-based FPGA accelerator for large-scale convolution neuron networks D Wang, J An, K Xu arXiv preprint arXiv:1611.02450, 2016 | 48 | 2016 |
| ABM-SpConv: A novel approach to FPGA-based acceleration of convolutional neural network inference D Wang, K Xu, Q Jia, S Ghiasi Proceedings of the 56th Annual Design Automation Conference 2019, 1-6, 2019 | 32 | 2019 |
| A dedicated hardware accelerator for real-time acceleration of YOLOv2 K Xu, X Wang, X Liu, C Cao, H Li, H Peng, D Wang Journal of Real-Time Image Processing 18, 481-492, 2021 | 30 | 2021 |
| GenExp: Multi-objective pruning for deep neural network based on genetic algorithm K Xu, D Zhang, J An, L Liu, L Liu, D Wang Neurocomputing 451, 81-94, 2021 | 27 | 2021 |
| DSP-efficient hardware acceleration of convolutional neural network inference on FPGAs D Wang, K Xu, J Guo, S Ghiasi IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 24 | 2020 |
| Fast and accurate object detection in remote sensing images based on lightweight deep neural network L Lang, K Xu, Q Zhang, D Wang Sensors 21 (16), 5460, 2021 | 20 | 2021 |
| A scalable OpenCL-based FPGA accelerator for YOLOv2 K Xu, X Wang, D Wang 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019 | 17 | 2019 |
| Globally soft filter pruning for efficient convolutional neural networks K Xu, X Wang, Q Jia, J An, D Wang | 6 | 2018 |
| An OpenCL-based FPGA accelerator for Faster R-CNN J An, D Zhang, K Xu, D Wang Entropy 24 (10), 1346, 2022 | 5 | 2022 |
| Adaptive linear unit for accurate binary neural networks R Mo, K Xu, L Liu, L Liu, D Wang 2022 16th IEEE International Conference on Signal Processing (ICSP) 1, 223-228, 2022 | 4 | 2022 |
| An FPGA-based hardware accelerator for real-time block-matching and 3D filtering D Wang, J Xu, K Xu IEEE Access 8, 121987-121998, 2020 | 4 | 2020 |
| Eq-net: Elastic quantization neural networks K Xu, L Han, Y Tian, S Yang, X Zhang Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 3 | 2023 |
| TA-BiDet: Task-aligned binary object detector H Pu, K Xu, D Zhang, L Liu, L Liu, D Wang Neurocomputing 511, 337-352, 2022 | 3 | 2022 |
| MultiQuant: Training Once for Multi-Bit Quantization of Neural Networks K Xu, Q Feng, X Zhang, D Wang IJCAI, 2022 | 3 | 2022 |
| Accelerating block-matching and 3D filtering-based image denoising algorithm on FPGAs X Wang, K Xu, D Wang 2018 14th IEEE International Conference on Signal Processing (ICSP), 235-240, 2018 | 3 | 2018 |
| Boosting Neural Cognitive Diagnosis with Student’s Affective State Modeling S Wang, Z Zeng, X Yang, K Xu, X Zhang Proceedings of the AAAI Conference on Artificial Intelligence 38 (1), 620-627, 2024 | 1 | 2024 |
| Edge-wise one-level global pruning on NAS generated networks Q Feng, K Xu, Y Li, Y Sun, D Wang Chinese Conference on Pattern Recognition and Computer Vision (PRCV), 3-15, 2021 | 1 | 2021 |
| 基于指数移动平均知识蒸馏的神经网络低比特量化方法 JLKXD Wang)、 模式识别与人工智能 34 (6), 1143-1151, 2021 | 1 | 2021 |
Dong WangSchool of Computer Science and Information Technology, Beijing Jiaotong UniversityVerified email at bjtu.edu.cn
