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Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection 期刊论文
IEEE/CAA Journal of Automatica Sinica, 2024, 卷号: 11, 期号: 3, 页码: 673-689
作者:  Cong Pan;  Junran Peng;  Zhaoxiang Zhang
Adobe PDF(37784Kb)  |  收藏  |  浏览/下载：48/19  |  提交时间：2024/02/19
Monocular 3D object detection  normalizing flows  Swin Transformer  
GAIA-Universe: Everything is Super-Netify 期刊论文
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2023, 卷号: 45, 期号: 10, 页码: 11856-11868
作者:  Peng, Junran;  Chang, Qing;  Yin, Haoran;  Bu, Xingyuan;  Sun, Jiajun;  Xie, Lingxi;  Zhang, Xiaopeng;  Tian, Qi;  Zhang, Zhaoxiang
收藏  |  浏览/下载：82/0  |  提交时间：2023/11/16
Computer vision  object detection  semantic segmentation  AutoML  
Delving into the Effectiveness of Receptive Fields: Learning Scale-Transferrable Architectures for Practical Object Detection 期刊论文
INTERNATIONAL JOURNAL OF COMPUTER VISION, 2022, 卷号: 130, 期号: 4, 页码: 970-989
作者:  Zhang, Zhaoxiang;  Pan, Cong;  Peng, Junran
收藏  |  浏览/下载：182/0  |  提交时间：2022/06/06
Computer vision  Object detection  Effective receptive fields  Hardware acceleration  
Fast Object Detection at Constrained Energy 期刊论文
IEEE Trans. on Emerging Topics in Computing, 2016, 期号: 1-1, 页码: 99
作者:  Jingyu Liu;  Yongzhen Huang;  Junran Peng;  Jun Yao;  Liang Wang
浏览  |  Adobe PDF(2002Kb)  |  收藏  |  浏览/下载：272/88  |  提交时间：2018/01/03
Object Detection  Constrained Energy  Fast-rcnn  
Exponential stability of Cohen-Grossberg neural networks with a general class of activation functions 期刊论文
PHYSICS LETTERS A, 2006, 卷号: 350, 期号: 1-2, 页码: 96-102
作者:  Wan, AH;  Wang, MS;  Peng, J;  Qiao, H
收藏  |  浏览/下载：184/0  |  提交时间：2015/11/08
Cohen-grossberg Neural Networks  Exponential Stability  Exponential Decay Estimate  Nonlinear Measure  
A reference model approach to stability analysis of neural networks 期刊论文
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS, 2003, 卷号: 33, 期号: 6, 页码: 925-936
作者:  Qiao, H;  Peng, J;  Xu, ZB;  Zhang, B
收藏  |  浏览/下载：189/0  |  提交时间：2016/12/07
Local Field Neural Network Model  Reference Model Approach  Stability Analysis  Static Neural Network Model  
Nonlinear measures: A new approach to exponential stability analysis for Hopfield-type neural networks 期刊论文
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2001, 卷号: 12, 期号: 2, 页码: 360-370
作者:  Qiao, H;  Peng, J;  Xu, ZB
收藏  |  浏览/下载：138/0  |  提交时间：2016/12/05
Global Exponential Stability  Hopfield-type Neural Networks  Local Exponential Stability  Matrix Measure  Nonlinear Measures