Computer Science ›› 2018, Vol. 45 ›› Issue (6A): 230-233.
• Pattern Recognition & Image Processing • Previous Articles Next Articles
LEI Qian, HAO Cun-ming,ZHANG Wei-ping
CLC Number:
| [1]BUCH N,VELASTIN S A,ORWELL J.A review of computer vision techniques for the analysis of urban traffic[J].IEEE Transactions on Intelligent Transportation Systems,2011,12(3):920-939. [2]DALAL N,TRIGGS B,SCHMID C.Human detection using orien- ted histograms of flow and appearance[C]∥European Confe-rence on Computer Vision.2006:428-441. [3]LOWE D G.Distinctive image features from scale-invariant keypoints[J].Kluwer Academic Publishers,2004,60(2):91-110. [4]MA X,GRIMSON W.Edge-based rich representation for vehicle classification[C]∥Tenth IEEE International Conference on Computer Vision.2005:1185-1192. [5]OJALA T,PIETIK,INEN M,et al.Multiresolution gray-scale and rotation invariant texture classification with local binary patterns[C]∥IEEE Transactions on Pattern Analysis and Machine Intelligence.2002:971-987. [6]ZHANG L,LI S Z,YUAN X,et al.Real-time object classification in video surveillance based on appearance learning[C]∥IEEE Conference on Computer Vision & Pattern Recognition.2007:1-8. [7]孙志军,薛磊,许阳明,等.深度学习研究综述[J].计算机研究应用,2012,29(8):2805-2810. [8]HINTON G E,SALAKHUTDINOV P R.Reducing the dimensionality of data with neural networks[J].Science,2006,313(5786):504-507. [9]沈焕锋,李平湘,张良培,等.图像超分辨率重建技术与方法综述[J].Optical Technique,2009,35(2):196-203. [10]YANG J C,WRIGHT J,HUANG T,et al.Image super-resolution as sparse representation of raw image patches[C]∥IEEE Conference of Computer Vision and Pattern Recognition (CVPR).2008:1-8. [11]CHO K.Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Noisy Images[C]∥Proceedings of the 30th International Conference on Machine Learning (ICML-13).2013:432-440. [12]ALAIN D,OLIVIER S.Gated Autoencoders with Tied Input Weights[C]∥International Conference on Machine Learning.2013:154-162. [13]VINCENT P,LAROCHELLE H,BENGIO Y,et al.Extracting and composing robust features with denoising autoencoders[C]∥International Conference on Machine Learning.2008:1096-1103. [14]TRIESCH J.A gradient rule for the plasticity of a neuron’s intrinsic excitability[C]∥International Conference on Artificial Neural Networks:Biological Inspirations.Springer-Verlag,2005:65-70. [15]YANG J C,WANG Z W,LIN Z,et al.Coupled dictionary trai- ning for image super-resolution[C]∥IEEE Transactions on Image Processing.2012:2359-2390. [16]JIA Y,SHELHAMER E,DONAHUE J,et al.Caffe:Convolutional Architecture for Fast Feature Embedding[J].Eprint Ar-xiv,2014:675-678. [9]LU Y,WANG Z.Detecting Driver Yawning in Successive Images[C]∥International Conference on Bioinformatics and Biomedical Engineering.IEEE Xplore,2007:581-583. [10]IBRAHIM M M,SORAGHAN J J,PETROPOULAKIS L,et al.Yawn analysis with mouth occlusion detection[J].Biomedical Signal Processing & Control,2015,18:360-369. [11]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(Z11):56-58. [12]CUN Y L,BOSER B,DENKER J,et al.Handwritten digit re- cognition with a backpropogation network[J].World of Computer Science & Information Technology Journal,1990,2(2):396-404. [13]ABTAHI S,OMIDYEGANEH M,SHIRMOHAMMADI S,et al.YawDD:A Yawning Detection DataSet[C]∥Proceedings of the 5th ACM Multimedia Systems Conference.New York:ACM Press,2014:24-28. [14]曹莹,苗启广,刘家辰,等.AdaBoost算法研究进展与展望[J].自动化学报,2013,39(6):745-758. [15]王平,全吉成,赵柏宇.基于双线性插值的图像缩放在GPU上的实现[J].微电子学与计算机,2016,33(11):129-132. [16]刘春晓,朱臻阳,伍敏,等.基于主色检测与灰度传播的彩色图像灰度化方法[J].计算机辅助设计与图形学学报,2016,28(3):433-442. [17]VOLOSHYN D.Application of deep learning and computer vision frameworks for solving video context prediction problem [C]∥Proceedings of the 10th International Conference of Programming.2016:164-169. [18]ZHANG W,YI L M,WANG T,et al.Driver yawning detection based on deep convolutional neural learning and robust nose tracking[C]∥International Joint Conference on Neural Networks.IEEE,2015:1-8. |
| [1] | 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. |
| [2] | 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. |
| [3] | 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. |
| [4] | 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. |
| [5] | HAO Zhi-rong, CHEN Long, HUANG Jia-cheng. Class Discriminative Universal Adversarial Attack for Text Classification [J]. Computer Science, 2022, 49(8): 323-329. |
| [6] | 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. |
| [7] | 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. |
| [8] | 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. |
| [9] | DAI Zhao-xia, LI Jin-xin, ZHANG Xiang-dong, XU Xu, MEI Lin, ZHANG Liang. Super-resolution Reconstruction of MRI Based on DNGAN [J]. Computer Science, 2022, 49(7): 113-119. |
| [10] | CHENG Cheng, JIANG Ai-lian. Real-time Semantic Segmentation Method Based on Multi-path Feature Extraction [J]. Computer Science, 2022, 49(7): 120-126. |
| [11] | HOU Yu-tao, ABULIZI Abudukelimu, ABUDUKELIMU Halidanmu. Advances in Chinese Pre-training Models [J]. Computer Science, 2022, 49(7): 148-163. |
| [12] | 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. |
| [13] | 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. |
| [14] | LIU Wei-ye, LU Hui-min, LI Yu-peng, MA Ning. Survey on Finger Vein Recognition Research [J]. Computer Science, 2022, 49(6A): 1-11. |
| [15] | SUN Fu-quan, CUI Zhi-qing, ZOU Peng, ZHANG Kun. Brain Tumor Segmentation Algorithm Based on Multi-scale Features [J]. Computer Science, 2022, 49(6A): 12-16. |
|
||
Home