Qingming Huang spends much of his time researching Artificial intelligence, Pattern recognition, Computer vision, Feature extraction and Video tracking. His Machine learning research extends to Artificial intelligence, which is thematically connected. His Pattern recognition study integrates concerns from other disciplines, such as Feature and Visual Word.
His research integrates issues of Salient, Viterbi algorithm and Identification in his study of Computer vision. Qingming Huang has included themes like Artificial neural network, Cluster analysis, Robustness and Salience in his Feature extraction study. His Video tracking research incorporates elements of Object detection, Multimedia and Human–computer interaction.
Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Feature extraction are his primary areas of study. His studies in Feature, Discriminative model, Contextual image classification, Object and Video tracking are all subfields of Artificial intelligence research. His research in Pattern recognition intersects with topics in Image, Representation and Visual Word.
His study in Object detection, Pixel, Image segmentation, Tracking and Motion estimation is done as part of Computer vision. The study incorporates disciplines such as Crowdsourcing and Data mining in addition to Machine learning. His Feature extraction study combines topics from a wide range of disciplines, such as Visualization, Robustness and Salience.
Qingming Huang focuses on Artificial intelligence, Pattern recognition, Machine learning, Computer vision and Feature extraction. Artificial intelligence is a component of his Feature, Convolutional neural network, Object, Benchmark and Discriminative model studies. His work in Pattern recognition addresses subjects such as Image, which are connected to disciplines such as Consistency.
His Machine learning study combines topics in areas such as Crowdsourcing and Path. When carried out as part of a general Computer vision research project, his work on Video tracking and Motion is frequently linked to work in Drone, therefore connecting diverse disciplines of study. The Feature extraction study combines topics in areas such as Artificial neural network, Visualization, Deep learning and Salience.
Qingming Huang mainly investigates Artificial intelligence, Pattern recognition, Feature extraction, Computer vision and Benchmark. Qingming Huang integrates many fields in his works, including Artificial intelligence and Code. His work on Discriminative model, Classifier and Image segmentation as part of general Pattern recognition study is frequently connected to Invariant, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Feature extraction study incorporates themes from Data mining, Artificial neural network, Image, Salience and Robustness. The various areas that Qingming Huang examines in his Benchmark study include Tracking, Representation and Saliency map. His research investigates the connection between Convolutional neural network and topics such as Eye tracking that intersect with problems in Video tracking.
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The Visual Object Tracking VOT2016 Challenge Results
Matej Kristan;Aleš Leonardis;Jiři Matas;Michael Felsberg.
european conference on computer vision (2016)
The Visual Object Tracking VOT2017 Challenge Results
Matej Kristan;Ales Leonardis;Jiri Matas;Michael Felsberg.
international conference on computer vision (2017)
Hedged Deep Tracking
Yuankai Qi;Shengping Zhang;Lei Qin;Hongxun Yao.
computer vision and pattern recognition (2016)
Fast and robust text detection in images and video frames
Qixiang Ye;Qingming Huang;Wen Gao;Debin Zhao.
Image and Vision Computing (2005)
CenterNet: Keypoint Triplets for Object Detection
Kaiwen Duan;Song Bai;Lingxi Xie;Honggang Qi.
international conference on computer vision (2019)
The Visual Object Tracking VOT2014 challenge results
Matej Kristan;Roman P. Pflugfelder;Ales Leonardis;Jiri Matas.
european conference on computer vision (2014)
Descriptive visual words and visual phrases for image applications
Shiliang Zhang;Qi Tian;Gang Hua;Qingming Huang.
acm multimedia (2009)
A configurable method for multi-style license plate recognition
Jianbin Jiao;Qixiang Ye;Qingming Huang.
Pattern Recognition (2009)
Using Webcast Text for Semantic Event Detection in Broadcast Sports Video
Changsheng Xu;Yi-Fan Zhang;Guangyu Zhu;Yong Rui.
IEEE Transactions on Multimedia (2008)
Measuring visual saliency by Site Entropy Rate
Wei Wang;Yizhou Wang;Qingming Huang;Wen Gao.
computer vision and pattern recognition (2010)
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