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ORCIDPattern Recognition Letters, Volume 86
Volume 86, January 2017
- Pradeep Kumar, Himaanshu Gauba
, Partha Pratim Roy, Debi Prosad Dogra:
Coupled HMM-based multi-sensor data fusion for sign language recognition. 1-8 - D. Selvathi, S. Bama:
Phase based distance regularized level set for the segmentation of ultrasound kidney images. 9-17 - Hongjun Zhou, Mingyu You, Lei Liu, Chao Zhuang:
Sequential data feature selection for human motion recognition via Markov blanket. 18-25 - Xiaohua Xia, Gang Dang, Yunshi Yao, Jia Liang:
Image registration model and algorithm for multi-focus images. 26-30 - Edras Reily Pacola, Veronica Quandt, Paulo Liberalesso, Sérgio Francisco Pichorim, Fabio Kurt Schneider, Humberto R. Gamba:
A versatile EEG spike detector with multivariate matrix of features based on the linear discriminant analysis, combined wavelets, and descriptors. 31-37 - Jérôme Gilles, Nicholas B. Ferrante:
Open Turbulent Image Set (OTIS). 38-41 - Van Cuong Kieu, Florence Cloppet, Nicole Vincent:
Adaptive fuzzy model for blur estimation on document images. 42-48 - Bassem Ben Cheikh, Étienne Baudrier, Gabriel Frey:
A tomographical reconstruction method from unknown direction projections for 2D gray-level images. 49-55 - Jongkwang Hong, Yongwon Hong, Youngjung Uh, Hyeran Byun:
Discovering overlooked objects: Context-based boosting of object detection in indoor scenes. 56-61 - Vikas Kumar, Arun K. Pujari, Sandeep Kumar Sahu, Venkateswara Rao Kagita, Vineet Padmanabhan:
Proximal maximum margin matrix factorization for collaborative filtering. 62-67 - F. A. Guerrero-Peña, Germano C. Vasconcelos:
Object recognition under severe occlusions with a hidden Markov model approach. 68-75 - Shaojie Chen, Kai Liu, Yuguang Yang, Yuting Xu, Seonjoo Lee, Martin A. Lindquist, Brian S. Caffo, Joshua T. Vogelstein:
An M-estimator for reduced-rank system identification. 76-81
- Alvaro Pardo, Josef Kittler:
Special section: CIARP 2015. 82 - Levi O. Vasconcelos, Erickson R. Nascimento, Mario F. M. Campos:
KVD: Scale invariant keypoints by combining visual and depth data. 83-89
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