2021 - IEEE Fellow For contributions to multimedia transmission and content analysis
Jianfei Cai spends much of his time researching Artificial intelligence, Computer vision, Pattern recognition, Machine learning and Deep learning. His study involves RGB color model, Convolutional neural network, Feature, Object and Image, a branch of Artificial intelligence. His Computer vision research focuses on subjects like Video quality, which are linked to Frame rate, Scalable Video Coding, Adaptation and Wireless network.
Jianfei Cai interconnects Cognitive neuroscience of visual object recognition, Key and Task in the investigation of issues within Pattern recognition. His Machine learning research incorporates themes from Object detection, Bayesian inference, Sparse approximation, Global Positioning System and Big data. His Deep learning research incorporates elements of Artificial neural network and Face.
Artificial intelligence, Computer vision, Pattern recognition, Computer network and Segmentation are his primary areas of study. Artificial intelligence connects with themes related to Machine learning in his study. His work carried out in the field of Pattern recognition brings together such families of science as Cognitive neuroscience of visual object recognition and Feature.
His Computer network research includes themes of Wireless, Wireless network, Real-time computing and Communication channel. Jianfei Cai combines subjects such as Frame, Transmission, Constant bitrate, Scalable Video Coding and Bandwidth with his study of Real-time computing. His research integrates issues of Algorithm and Error detection and correction in his study of Communication channel.
Jianfei Cai mainly investigates Artificial intelligence, Pattern recognition, Computer vision, Image and Closed captioning. His Artificial intelligence study typically links adjacent topics like Machine learning. His Pattern recognition research includes themes of Detector, Object detection and Feature.
His studies in Computer vision integrate themes in fields like Representation, Identity and Graph. His study focuses on the intersection of Image and fields such as Domain with connections in the field of Image translation. The various areas that Jianfei Cai examines in his Closed captioning study include Sentence, Natural language processing, Encoder and Speech recognition.
Jianfei Cai mostly deals with Artificial intelligence, Pattern recognition, Computer vision, Deep learning and Closed captioning. In his work, Pose is strongly intertwined with Graph, which is a subfield of Artificial intelligence. The Pattern recognition study combines topics in areas such as Contextual image classification, Cognitive neuroscience of visual object recognition and Minimum bounding box.
His work on Iterative reconstruction and Human motion as part of general Computer vision study is frequently connected to Joint, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them. His Deep learning study integrates concerns from other disciplines, such as Relation, Facial expression, Face and Benchmark. Jianfei Cai has included themes like Sentence and Natural language processing in his Closed captioning study.
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Recent advances in convolutional neural networks
Jiuxiang Gu;Zhenhua Wang;Jason Kuen;Lianyang Ma.
Pattern Recognition (2018)
Joint source channel rate-distortion analysis for adaptive mode selection and rate control in wireless video coding
Zhihai He;Jianfei Cai;Chang Wen Chen.
IEEE Transactions on Circuits and Systems for Video Technology (2002)
Admission control in IEEE 802.11e wireless LANs
Deyun Gao;Jianfei Cai;King Ngi Ngan.
IEEE Network (2005)
Beyond pixels: A comprehensive survey from bottom-up to semantic image segmentation and cosegmentation
Hongyuan Zhu;Fanman Meng;Jianfei Cai;Shijian Lu.
Journal of Visual Communication and Image Representation (2016)
Auto-Encoding Scene Graphs for Image Captioning
Xu Yang;Kaihua Tang;Hanwang Zhang;Jianfei Cai.
computer vision and pattern recognition (2019)
Look, Imagine and Match: Improving Textual-Visual Cross-Modal Retrieval with Generative Models
Jiuxiang Gu;Jianfei Cai;Shafiq Joty;Li Niu.
computer vision and pattern recognition (2018)
User-Friendly Interactive Image Segmentation Through Unified Combinatorial User Inputs
Wenxian Yang;Jianfei Cai;Jianmin Zheng;Jiebo Luo.
IEEE Transactions on Image Processing (2010)
Recent Advances in Convolutional Neural Networks
Jiuxiang Gu;Zhenhua Wang;Jason Kuen;Lianyang Ma.
arXiv: Computer Vision and Pattern Recognition (2015)
Large-Margin Multi-Modal Deep Learning for RGB-D Object Recognition
Anran Wang;Jiwen Lu;Jianfei Cai;Tat-Jen Cham.
IEEE Transactions on Multimedia (2015)
HMM-Based audio keyword generation
Min Xu;Ling-Yu Duan;Jianfei Cai;Liang-Tien Chia.
advances in multimedia (2004)
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