2006 - IEEE Fellow For contributions to performance analysis systems and jammer suppression in communication systems.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Feature extraction, Feature and Computer vision. The Artificial intelligence study combines topics in areas such as Frame and Machine learning. His Pattern recognition research includes themes of Image quality and Fingerprint.
His study in Feature extraction is interdisciplinary in nature, drawing from both Artificial neural network, Facial recognition system and Hidden Markov model. His Feature study incorporates themes from Image segmentation, Digital image, Representation, Matching and Demosaicing. His Computer vision research incorporates elements of Distortion and Binary number.
His main research concerns Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Algorithm. Within one scientific family, Alex C. Kot focuses on topics pertaining to Machine learning under Artificial intelligence, and may sometimes address concerns connected to Benchmark. His Pattern recognition study integrates concerns from other disciplines, such as Image processing, Image restoration, Facial recognition system and Fingerprint.
His Computer vision research is multidisciplinary, relying on both Distortion and Binary number. His biological study spans a wide range of topics, including Visualization, Feature, Discriminative model and Convolutional neural network. While the research belongs to areas of Algorithm, Alex C. Kot spends his time largely on the problem of Electronic engineering, intersecting his research to questions surrounding Communication channel.
His primary areas of study are Artificial intelligence, Pattern recognition, Machine learning, Feature and Feature extraction. His work on Artificial intelligence is being expanded to include thematically relevant topics such as Computer vision. The various areas that Alex C. Kot examines in his Pattern recognition study include 3D pose estimation and Boosting.
His Machine learning research is multidisciplinary, incorporating perspectives in Adversarial system, Sample and Robustness. His Feature research includes elements of Motion, Representation, Matching, Feature learning and Generalization. His Feature extraction study combines topics in areas such as Visualization, Coding, Information retrieval and Hidden Markov model.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Feature extraction, Feature and Benchmark. His studies deal with areas such as Focus, Machine learning and Generalization as well as Artificial intelligence. Alex C. Kot combines subjects such as Image and Spoofing attack with his study of Pattern recognition.
In his study, Prior probability and Image processing is strongly linked to Content, which falls under the umbrella field of Image. His Feature extraction study combines topics from a wide range of disciplines, such as Distributed computing, Artificial neural network, Lossless compression, Visualization and Hidden Markov model. His Feature research integrates issues from Matching, Regularization, Representation and Training set.
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.
Global Context-Aware Attention LSTM Networks for 3D Action Recognition
Jun Liu;Gang Wang;Ping Hu;Ling-Yu Duan.
computer vision and pattern recognition (2017)
Domain Generalization with Adversarial Feature Learning
Haoliang Li;Sinno Jialin Pan;Shiqi Wang;Alex C. Kot.
computer vision and pattern recognition (2018)
NTU RGB+D 120: A Large-Scale Benchmark for 3D Human Activity Understanding
Jun Liu;Amir Shahroudy;Mauricio Perez;Gang Wang.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2020)
Eigenfeature Regularization and Extraction in Face Recognition
Xudong Jiang;B. Mandal;A. Kot.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)
Dual Attention Matching Network for Context-Aware Feature Sequence Based Person Re-identification
Jianlou Si;Honggang Zhang;Chun-Guang Li;Jason Kuen.
computer vision and pattern recognition (2018)
Skeleton-Based Human Action Recognition With Global Context-Aware Attention LSTM Networks
Jun Liu;Gang Wang;Ling-Yu Duan;Kamila Abdiyeva.
IEEE Transactions on Image Processing (2018)
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
Jun Liu;Amir Shahroudy;Dong Xu;Alex C. Kot.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2018)
Errata to “Nonlinear Dynamic System Identification Using Chebyshev Functional Link Artificial Neural Networks”
J.C. Patra;A.C. Kot.
systems man and cybernetics (2002)
Two-Dimensional Polar Harmonic Transforms for Invariant Image Representation
Pew-Thian Yap;Xudong Jiang;Alex Chichung Kot.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2010)
Quality Measures of Fingerprint Images
LinLin Shen;Alex ChiChung Kot;Wai Mun Koo.
Lecture Notes in Computer Science (2001)
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