Pattern Recognition, Volume 77

Volume 77, May 2018

Classifiers and classification

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  Fatemeh Ghofrani, Alireza Keshavarz-Haddad, Ali Jamshidi:
  A new probabilistic classifier based on decomposable models with application to internet traffic. 1-11

Clustering

• 
  Qi Tan, Pei Yang, Jingrui He:
  Feature co-shrinking for co-clustering. 12-19

Features

• 
  Kangfeng Zheng, Xiujuan Wang:
  Feature selection method with joint maximal information entropy between features and class. 20-29

Classifiers and classification

• 
  Josef Kittler, Cemre Zor, Ioannis Kaloskampis, Yulia Hicks, Wenwu Wang:
  Error sensitivity analysis of Delta divergence - a novel measure for classifier incongruence detection. 30-44
• 
  Konstantin S. Amelin, Oleg N. Granichin, Natalia Kizhaeva, Zeev Volkovich:
  Patterning of writing style evolution by means of dynamic similarity. 45-64

Machine learning

• 
  Seongyoun Woo, Chulhee Lee:
  Incremental feature extraction based on decision boundaries. 65-74

Human movements and activities

• 
  Wenwen Ding, Kai Liu, Evgeny Belyaev, Fei Cheng:
  Tensor-based linear dynamical systems for action recognition from 3D skeletons. 75-86

Machine learning

• 
  Baochang Zhang, Alessandro Perina, Ce Li, Qixiang Ye, Vittorio Murino, Alessio Del Bue:
  Manifold constraint transfer for visual structure-driven optimization. 87-98

Various applications

• 
  Sadegh Etemad, Maryam Amirmazlaghani:
  A new multiplicative watermark detector in the contourlet domain using t Location-Scale distribution. 99-112

Objects and image analysis

• 
  Yansheng Li, Yongjun Zhang:
  Robust infrared small target detection using local steering kernel reconstruction. 113-125

Clustering

• 
  Tianchi Liu, Chamara Kasun Liyanaarachchi Lekamalage, Guang-Bin Huang, Zhiping Lin:
  An adaptive graph learning method based on dual data representations for clustering. 126-139

Classifiers and classification

• 
  Kan Hong, Guodong Liu, Wentao Chen, Sheng Hong:
  Classification of the emotional stress and physical stress using signal magnification and canonical correlation analysis. 140-149

Objects and image analysis

• 
  Chen Qin, Ricardo Guerrero, Christopher Bowles, Liang Chen, David Alexander Dickie, Maria del C. Valdés Hernández, Joanna M. Wardlaw, Daniel Rueckert:
  A large margin algorithm for automated segmentation of white matter hyperintensity. 150-159

Virtual Special Section on Deep Learning for Computer Aided Cancer Detection and Diagnosis with Medical Imaging

• 
  Xiaohui Yuan, Lijun Xie, Mohamed Abouelenien:
  A regularized ensemble framework of deep learning for cancer detection from multi-class, imbalanced training data. 160-172

Objects and image analysis

• 
  Guijin Wang, Wentao Li, Xuanwu Yin, Huazhong Yang:
  All-in-focus with directional-max-gradient flow and labeled iterative depth propagation. 173-187

Clustering

• 
  Jian Yu, Chaomurilige Wang, Miin-Shen Yang:
  On convergence and parameter selection of the EM and DA-EM algorithms for Gaussian mixtures. 188-203

Classifiers and classification

• 
  Marcelino Lázaro, Monson H. Hayes, Aníbal R. Figueiras-Vidal:
  Training neural network classifiers through Bayes risk minimization applying unidimensional Parzen windows. 204-215

Virtual Special Section on Articulated Motion and Deformable Objects

• 
  Longbo Kong, Xiaohui Yuan, Amar Man Maharjan:
  A hybrid framework for automatic joint detection of human poses in depth frames. 216-225

Classifiers and classification

• 
  Melih Kandemir, Taygun Kekeç, Reyyan Yeniterzi:
  Supervising topic models with Gaussian processes. 226-236

Objects and image analysis

• 
  Daniela Portes L. Ferreira, Eraldo Ribeiro, Célia A. Zorzo Barcelos:
  A variational approach to non-rigid image registration with Bregman divergences and multiple features. 237-247
• 
  Sergey Kosov, Kimiaki Shirahama, Chen Li, Marcin Grzegorzek:
  Environmental microorganism classification using conditional random fields and deep convolutional neural networks. 248-261

Bio-medical patterns

• 
  Xinglong Liu, Fei Hou, Hong Qin, Aimin Hao:
  Multi-view multi-scale CNNs for lung nodule type classification from CT images. 262-275

Face and biometrics

• 
  Ce Li, Chunyu Xie, Baochang Zhang, Chen Chen, Jungong Han:
  Deep Fisher discriminant learning for mobile hand gesture recognition. 276-288
• 
  Amir Anees, Yi-Ping Phoebe Chen:
  Discriminative binary feature learning and quantization in biometric key generation. 289-305

Virtual Special Section on Pattern Recognition for High Performance Imaging

• 
  Cheng Deng, Xianglong Liu, Chao Li, Dacheng Tao:
  Active multi-kernel domain adaptation for hyperspectral image classification. 306-315

Features

• 
  Tong Qiao, Zhijing Yang, Jinchang Ren, Peter W. T. Yuen, Huimin Zhao, Genyun Sun, Stephen Marshall, Jón Atli Benediktsson:
  Joint bilateral filtering and spectral similarity-based sparse representation: A generic framework for effective feature extraction and data classification in hyperspectral imaging. 316-328

Machine learning

• 
  Marc-André Carbonneau, Veronika Cheplygina, Eric Granger, Ghyslain Gagnon:
  Multiple instance learning: A survey of problem characteristics and applications. 329-353
• 
  Jiuxiang Gu, Zhenhua Wang, Jason Kuen, Lianyang Ma, Amir Shahroudy, Bing Shuai, Ting Liu, Xingxing Wang, Gang Wang, Jianfei Cai, Tsuhan Chen:
  Recent advances in convolutional neural networks. 354-377
• 
  Jicong Fan, Tommy W. S. Chow:
  Non-linear matrix completion. 378-394

Handwriting and document analysis

• 
  Shuangping Huang, Zhuoyao Zhong, Lianwen Jin, Shuye Zhang, Haobin Wang:
  DropRegion training of inception font network for high-performance Chinese font recognition. 395-411

Classifiers and classification

• 
  Benjamin Quost, Sébastien Destercke:
  Classification by pairwise coupling of imprecise probabilities. 412-425

Face and biometrics

• 
  Weihong Deng, Jiani Hu, Zhongjun Wu, Jun Guo:
  From one to many: Pose-Aware Metric Learning for single-sample face recognition. 426-437

Classifiers and classification

• 
  Jianlong Chang, Lingfeng Wang, Gaofeng Meng, Shiming Xiang, Chunhong Pan:
  Deep unsupervised learning with consistent inference of latent representations. 438-453

Errata and comments

• 
  Yahya Forghani:
  Comment on "Joint sparse principal component analysis" by S. Yi et al. (Pattern Recognition, vol. 61 pp. 524-536, 2017). 454-455
• 
  Yahya Forghani:
  Comment on "Enhanced soft subspace clustering integrating within-cluster and between-cluster information" by Z. Deng et al. (Pattern Recognition, vol. 43 pp. 767-781, 2010). 456-457
• 
  Xuan Wang, Guanghui Shi, Fang-xia Guo:
  A comment on "Translation and scale invariants of Tchebichef moments" by Hongqing Zhu [Pattern Recognition 40 (2007) 2530-2542]. 458-463
• 
  Anandarup Roy, Anabik Pal, Utpal Garain:
  Erratum to "JCLMM: A finite mixture model for clustering of circular-linear data and its application to psoriatic plaque segmentation" [Pattern Recognition 66 (2017) 160-173]. 464