His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Facial recognition system and Feature extraction. His Artificial intelligence study frequently draws connections to adjacent fields such as Machine learning. His studies in Pattern recognition integrate themes in fields like Speech recognition, Facial expression and Face.
The various areas that Liming Chen examines in his Computer vision study include Robustness and Pattern recognition. His Facial recognition system research is multidisciplinary, incorporating perspectives in Video tracking and Mean curvature. In his research, Feature selection is intimately related to Depth map, which falls under the overarching field of Feature extraction.
Liming Chen mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Facial recognition system and Face. His Machine learning research extends to the thematically linked field of Artificial intelligence. Liming Chen has included themes like Contextual image classification and Histogram in his Pattern recognition study.
His research related to Face hallucination, Face detection, Video tracking, Local binary patterns and Pixel might be considered part of Computer vision. His studies deal with areas such as Sparse approximation, Robustness and Image texture as well as Facial recognition system. His Feature extraction research is multidisciplinary, incorporating elements of Feature and Support vector machine.
His primary areas of study are Artificial intelligence, Pattern recognition, Composite material, Machine learning and Deep learning. His work in the fields of Artificial intelligence, such as Facial recognition system, Segmentation, Face and Robustness, intersects with other areas such as Expression. His Facial recognition system research is classified as research in Computer vision.
Liming Chen combines subjects such as Encoder and Feature with his study of Pattern recognition. His research in the fields of Artificial neural network overlaps with other disciplines such as Identity. His Deep learning study integrates concerns from other disciplines, such as Image, Image retrieval, Information retrieval and Scripting language.
His main research concerns Composite material, Artificial intelligence, Energy absorption, Ultimate tensile strength and Fiber. His Modulus, Elastic modulus and Auxetics study, which is part of a larger body of work in Composite material, is frequently linked to Ring mode, bridging the gap between disciplines. The various areas that he examines in his Artificial intelligence study include Machine learning and Pattern recognition.
When carried out as part of a general Pattern recognition research project, his work on Discriminative model is frequently linked to work in Expression, therefore connecting diverse disciplines of study. His work carried out in the field of Ultimate tensile strength brings together such families of science as Volume fraction, Work and Fibre-reinforced plastic. As a member of one scientific family, Liming Chen mostly works in the field of Fiber, focusing on Stress and, on occasion, Composite number, Compression and Viscoelasticity.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
Di Huang;Caifeng Shan;M. Ardabilian;Yunhong Wang.
systems man and cybernetics (2011)
LIRIS-ACCEDE: A Video Database for Affective Content Analysis
Yoann Baveye;Emmanuel Dellandrea;Christel Chamaret;Liming Chen.
IEEE Transactions on Affective Computing (2015)
WebGuard: a Web filtering engine combining textual, structural, and visual content-based analysis
M. Hammami;Y. Chahir;L. Chen.
IEEE Transactions on Knowledge and Data Engineering (2006)
A robust agorithm for eye detection on gray intensity face without spectacles
Kun Peng;Liming Chen;Su Ruan;Georgy Kukharev.
Journal of Computer Science and Technology (2005)
Image region description using orthogonal combination of local binary patterns enhanced with color information
Chao Zhu;Charles-Edmond Bichot;Liming Chen.
Pattern Recognition (2013)
A coarse-to-fine curvature analysis-based rotation invariant 3D face landmarking
Przemyslaw Szeptycki;Mohsen Ardabilian;Liming Chen.
international conference on biometrics theory applications and systems (2009)
Multi-scale Color Local Binary Patterns for Visual Object Classes Recognition
Chao Zhu;Charles-Edmond Bichot;Liming Chen.
international conference on pattern recognition (2010)
Gender identification using a general audio classifier
H. Harb;Liming Chen.
international conference on multimedia and expo (2003)
Multimodal 2D+3D Facial Expression Recognition With Deep Fusion Convolutional Neural Network
Huibin Li;Jian Sun;Zongben Xu;Liming Chen.
IEEE Transactions on Multimedia (2017)
3-D Face Recognition Using eLBP-Based Facial Description and Local Feature Hybrid Matching
Di Huang;M. Ardabilian;Yunhong Wang;Liming Chen.
IEEE Transactions on Information Forensics and Security (2012)
Profile was last updated on December 6th, 2021.
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