受强制性开放获取政策约束的文章 - Lianwen Jin了解详情
无法在其他位置公开访问的文章：79 篇
A new CNN-based method for multi-directional car license plate detection
L Xie, T Ahmad, L Jin, Y Liu, S Zhang
IEEE Transactions on Intelligent Transportation Systems 19 (2), 507-517, 2018
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Hierarchical deep reinforcement learning for continuous action control
Z Yang, K Merrick, L Jin, HA Abbass
IEEE transactions on neural networks and learning systems 29 (11), 5174-5184, 2018
强制性开放获取政策： Australian Research Council
Graph convolutional neural network for human action recognition: A comprehensive survey
T Ahmad, L Jin, X Zhang, S Lai, G Tang, L Lin
IEEE Transactions on Artificial Intelligence 2 (2), 128-145, 2021
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Chinese character-level writer identification using path signature feature, DropStroke and deep CNN
W Yang, L Jin, M Liu
2015 13th International Conference on Document Analysis and Recognition …, 2015
强制性开放获取政策： 国家自然科学基金委员会
Recurrent adaptation networks for online signature verification
S Lai, L Jin
IEEE Transactions on information forensics and security 14 (6), 1624-1637, 2018
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Facial attractiveness prediction using psychologically inspired convolutional neural network (PI-CNN)
J Xu, L Jin, L Liang, Z Feng, D Xie, H Mao
2017 IEEE international conference on acoustics, speech and signal …, 2017
强制性开放获取政策： 国家自然科学基金委员会
Multi-font printed Chinese character recognition using multi-pooling convolutional neural network
Z Zhong, L Jin, Z Feng
2015 13th International Conference on Document Analysis and Recognition …, 2015
强制性开放获取政策： 国家自然科学基金委员会
Applications of deep learning for handwritten Chinese character recognition: a review
J Lian-Wen, Z Zhuo-Yao, Y Zhao, Y Wei-Xin, X Ze-Cheng, S Jun
Acta Automatica Sinica 42 (8), 1125-1141, 2016
强制性开放获取政策： 国家自然科学基金委员会
OBC306: A large-scale oracle bone character recognition dataset
S Huang, H Wang, Y Liu, X Shi, L Jin
2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Erasenet: End-to-end text removal in the wild
C Liu, Y Liu, L Jin, S Zhang, C Luo, Y Wang
IEEE Transactions on Image Processing 29, 8760-8775, 2020
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
ICPR2018 contest on robust reading for multi-type web images
M He, Y Liu, Z Yang, S Zhang, C Luo, F Gao, Q Zheng, Y Wang, X Zhang, ...
2018 24th international conference on pattern recognition (ICPR), 7-12, 2018
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
STAN: A sequential transformation attention-based network for scene text recognition
Q Lin, C Luo, L Jin, S Lai
Pattern Recognition 111, 107692, 2021
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Arbitrarily shaped scene text detection with a mask tightness text detector
Y Liu, L Jin, C Fang
IEEE Transactions on Image Processing 29, 2918-2930, 2019
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Regression Guided by Relative Ranking Using Convolutional Neural Network (RCNN) for Facial Beauty Prediction
L Lin, L Liang, L Jin
IEEE Transactions on Affective Computing 13 (1), 122-134, 2019
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Encoding pathlet and SIFT features with bagged VLAD for historical writer identification
S Lai, Y Zhu, L Jin
IEEE Transactions on Information Forensics and Security 15, 3553-3566, 2020
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
OPMP: An omnidirectional pyramid mask proposal network for arbitrary-shape scene text detection
S Zhang, Y Liu, L Jin, Z Wei, C Shen
IEEE Transactions on Multimedia 23, 454-467, 2020
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
SCUT-HCCDoc: A new benchmark dataset of handwritten Chinese text in unconstrained camera-captured documents
H Zhang, L Liang, L Jin
Pattern Recognition 108, 107559, 2020
强制性开放获取政策： 国家自然科学基金委员会
Skeleton-based action recognition using sparse spatio-temporal GCN with edge effective resistance
T Ahmad, L Jin, L Lin, GZ Tang
Neurocomputing 423, 389-398, 2021
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
Large‐scale extraction of drug–disease pairs from the medical literature
P Wang, T Hao, J Yan, L Jin
Journal of the Association for Information Science and Technology 68 (11 …, 2017
强制性开放获取政策： 国家自然科学基金委员会
A fast and accurate fully convolutional network for end-to-end handwritten Chinese text segmentation and recognition
D Peng, L Jin, Y Wu, Z Wang, M Cai
2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019
强制性开放获取政策： US National Science Foundation, 国家自然科学基金委员会
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