Computer Science ›› 2019, Vol. 46 ›› Issue (5): 260-265.doi: 10.11896/j.issn.1002-137X.2019.05.040
Previous Articles Next Articles
XU Yi-ming, ZHANG Juan, LIU Cheng-cheng, GU Ju-ping, PAN Gao-chao
CLC Number:
[1]ZHANG H,WANG K F,WANG F Y.Advances and perspec-tives on applications of deep learning in visual object detection[J].Acta Automatica Sinica,2017,43(8):1289-1305.(in Chinese)张慧,王坤峰,王飞跃.深度学习在目标视觉检测中的应用进展与展望[J].自动化学报,2017,43(8):1289-1305. [2]WEI Y M.Research on aerial image location based on convolution neural network [J].Ship Electronic Engineering,2017,37(6):33-37.(in Chinese)魏湧明.基于卷积神经网络的航拍图像定位研究[J].舰船电子工程,2017,37(6):33-37. [3]SUN Z Y,LU C X,SHI Z Z,et al.Research and advances on deep learning [J].Computer Science,2016,43(2):1-8.(in Chinese)孙志远,鲁成祥,史忠植,等.深度学习研究与进展[J].计算机科学,2016,43(2):1-8. [4]GIRSHICK R,DONAHUE J,DARRELL T,et al.Rich feature hierarchies for accurate object detection and semantic segmentation[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Press,2014:580-587. [5]GIRSHICK R.Fast R-CNN[C]∥Proceedings of IEEE International Conference on Computer Vision.Chile:IEEE Press,2015:1440-1448. [6]REN S Q,HE K M,GIRSHICK R,et al.Faster R-CNN:to-wards real-time object detection with region proposal networks [J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(6):1137-1149. [7]SZEGEDY C,LIU W,JIA Y Q,et al.Going deeper with convolutions[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.USA:IEEE Press,2015:1-9. [8]LI Y D,HAO Z B,LEI H.Survey of convolutional neural network [J].Journal of Computer Applications,2016,36(9):2508-2515,2565.(in Chinese)李彦东,郝宗波,雷航.卷积神经网络研究综述[J].计算机应用,2016,36(9):2508-2515,2565. [9]ZHOU J Y,ZHAO Y M.Application of convolution neural network in image classification and object detection [J].Computer Engineering and Applications,2017,53(13):34-41.(in Chinese)周俊宇,赵艳明.卷积神经网络在图像分类和目标检测应用综述[J].计算机工程与应用,2017,53(13):34-41. [10]LI X D,YE M,LI T.Review of object detection based on convolutional neural networks [J].Application Research of Compu-ters,2017,34(10):2881-2886,2891.(in Chinese)李旭东,叶茂,李涛.基于卷积神经网络的目标检测研究综述[J].计算机应用研究,2017,34(10):2881-2886,2891. [11]WANG Z M,CAO H J,FAN L.Method on human activity re-cognition based on convolutional neural networks [J].Computer Science,2016,43(11A):56-58,87.(in Chinese)王忠民,曹洪江,范琳.一种基于卷积神经网络深度学习的人体行为识别方法[J].计算机科学,2016,43(11A):56-58,87. [12]FENG Y S,WANG Z L.Fine-grained image categorization with segmentation based on top-down attention map [J].Journal of Image and Graphics,2016,21(9):1147-1154.(in Chinese)冯语姗,王子磊.自上而下注意图分割的细粒度图像分类[J].中国图象图形学报,2016,21(9):1147-1154. [13]DAI C K,LI Y.Aeroplane detection in static aerodrome based on Faster RCNN and multi-part model[J].Journal of Computer Applications,2017,37(S2):85-88.(in Chinese)戴陈卡,李毅.基于Faster RCNN以及多部件结合的机场场面静态飞机检测[J].计算机应用,2017,37(S2):85-88. [14]PENG G,YANG S Q,HUANG X H,et al.Improved object detection method of micro-operating system based on regioncon-volutional neural network [J].Pattern Recognition and Artificial Intelligence,2018,31(2):142-149.(in Chinese)彭刚,杨诗琪,黄心汉,等.改进的基于区域卷积神经网络的微操作系统目标检测方法[J].模式识别与人工智能,2018,31(2):142-149. [15]ZHUANG F Z,LUO P,HE Q,et al.Survey on transfer learning research[J].Journal of Software,2015,26(1):26-39.(in Chinese)庄福振,罗平,何清,等.迁移学习研究与进展[J].软件学报,2015,26(1):26-39. [16]DAI W Y,YANG Q,XUE G R,et al.Boosting for transfer learning[C]∥Proceedings of International Conference on Machine Learning.USA:IEEE Press,2007:193-200. [17]WU L N,HUANG Y P,ZHENG X.Noval transfer learning algorithm based on bag-of-visual words model[J].ComputerScien-ce,2014,41(12):260-263,274.(in Chinese)吴丽娜,黄雅平,郑翔.基于词带模型的迁移学习算法[J].计算机科学,2014,41(12):260-263,274. |
[1] | ZHOU Le-yuan, ZHANG Jian-hua, YUAN Tian-tian, CHEN Sheng-yong. Sequence-to-Sequence Chinese Continuous Sign Language Recognition and Translation with Multi- layer Attention Mechanism Fusion [J]. Computer Science, 2022, 49(9): 155-161. |
[2] | XU Yong-xin, ZHAO Jun-feng, WANG Ya-sha, XIE Bing, YANG Kai. Temporal Knowledge Graph Representation Learning [J]. Computer Science, 2022, 49(9): 162-171. |
[3] | RAO Zhi-shuang, JIA Zhen, ZHANG Fan, LI Tian-rui. Key-Value Relational Memory Networks for Question Answering over Knowledge Graph [J]. Computer Science, 2022, 49(9): 202-207. |
[4] | TANG Ling-tao, WANG Di, ZHANG Lu-fei, LIU Sheng-yun. Federated Learning Scheme Based on Secure Multi-party Computation and Differential Privacy [J]. Computer Science, 2022, 49(9): 297-305. |
[5] | FANG Yi-qiu, ZHANG Zhen-kun, GE Jun-wei. Cross-domain Recommendation Algorithm Based on Self-attention Mechanism and Transfer Learning [J]. Computer Science, 2022, 49(8): 70-77. |
[6] | CHEN Yong-quan, JIANG Ying. Analysis Method of APP User Behavior Based on Convolutional Neural Network [J]. Computer Science, 2022, 49(8): 78-85. |
[7] | ZHU Cheng-zhang, HUANG Jia-er, XIAO Ya-long, WANG Han, ZOU Bei-ji. Deep Hash Retrieval Algorithm for Medical Images Based on Attention Mechanism [J]. Computer Science, 2022, 49(8): 113-119. |
[8] | SUN Qi, JI Gen-lin, ZHANG Jie. Non-local Attention Based Generative Adversarial Network for Video Abnormal Event Detection [J]. Computer Science, 2022, 49(8): 172-177. |
[9] | WANG Jian, PENG Yu-qi, ZHAO Yu-fei, YANG Jian. Survey of Social Network Public Opinion Information Extraction Based on Deep Learning [J]. Computer Science, 2022, 49(8): 279-293. |
[10] | HAO Zhi-rong, CHEN Long, HUANG Jia-cheng. Class Discriminative Universal Adversarial Attack for Text Classification [J]. Computer Science, 2022, 49(8): 323-329. |
[11] | JIANG Meng-han, LI Shao-mei, ZHENG Hong-hao, ZHANG Jian-peng. Rumor Detection Model Based on Improved Position Embedding [J]. Computer Science, 2022, 49(8): 330-335. |
[12] | HOU Yu-tao, ABULIZI Abudukelimu, ABUDUKELIMU Halidanmu. Advances in Chinese Pre-training Models [J]. Computer Science, 2022, 49(7): 148-163. |
[13] | ZHOU Hui, SHI Hao-chen, TU Yao-feng, HUANG Sheng-jun. Robust Deep Neural Network Learning Based on Active Sampling [J]. Computer Science, 2022, 49(7): 164-169. |
[14] | SU Dan-ning, CAO Gui-tao, WANG Yan-nan, WANG Hong, REN He. Survey of Deep Learning for Radar Emitter Identification Based on Small Sample [J]. Computer Science, 2022, 49(7): 226-235. |
[15] | HU Yan-yu, ZHAO Long, DONG Xiang-jun. Two-stage Deep Feature Selection Extraction Algorithm for Cancer Classification [J]. Computer Science, 2022, 49(7): 73-78. |
|