His main research concerns Artificial intelligence, Pattern recognition, Machine learning, Feature and Sparse approximation. His work in the fields of Feature extraction, Feature detection and Deep learning overlaps with other areas such as Adaptation and Generalization. His research integrates issues of Object, Kadir–Brady saliency detector, Motion and Conditional random field in his study of Feature extraction.
Yu-Chiang Frank Wang has included themes like Facial recognition system, Iterative reconstruction, Computer vision and Robustness in his Pattern recognition study. His research in Machine learning intersects with topics in Contextual image classification, Subspace topology and Classifier. His Statistical classification study combines topics in areas such as Variation, Classifier and Shot.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Computer vision, Machine learning and Image. His work is connected to Deep learning, Robustness, Sparse approximation, Feature and Feature extraction, as a part of Artificial intelligence. His studies in Feature extraction integrate themes in fields like Video tracking and Visualization.
The various areas that Yu-Chiang Frank Wang examines in his Pattern recognition study include Contextual image classification, Facial recognition system and Visual Word. Within one scientific family, Yu-Chiang Frank Wang focuses on topics pertaining to Training set under Machine learning, and may sometimes address concerns connected to Discriminative model. His Image research integrates issues from Iterative reconstruction, Task and Benchmark.
Yu-Chiang Frank Wang spends much of his time researching Artificial intelligence, Machine learning, Image, Visualization and Robustness. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Computer vision and Pattern recognition. His studies examine the connections between Pattern recognition and genetics, as well as such issues in Interpolation, with regards to MNIST database, Feature learning, Image warping, Feature and Autoencoder.
He interconnects Exploit and Training set in the investigation of issues within Machine learning. His work carried out in the field of Visualization brings together such families of science as Speech recognition, Inpainting, Consistency, Ground truth and Feature extraction. His work in Robustness addresses issues such as Task, which are connected to fields such as Content.
His primary areas of study are Artificial intelligence, Machine learning, Deep learning, Image translation and Segmentation. Yu-Chiang Frank Wang combines topics linked to Audio visual with his work on Artificial intelligence. His work on Re identification is typically connected to Matching as part of general Machine learning study, connecting several disciplines of science.
His study focuses on the intersection of Segmentation and fields such as Data point with connections in the field of Feature extraction and Kernel. He has included themes like Supervised learning, Similarity and Image retrieval in his Representation study. His Robustness study incorporates themes from Network architecture, Image manipulation, External Data Representation and Data domain.
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A Closer Look at Few-shot Classification
Wei-Yu Chen;Yen-Cheng Liu;Zsolt Kira;Yu-Chiang Frank Wang.
international conference on learning representations (2019)
No More Discrimination: Cross City Adaptation of Road Scene Segmenters
Yi-Hsin Chen;Wei-Yu Chen;Yu-Ting Chen;Bo-Cheng Tsai.
international conference on computer vision (2017)
Low-rank matrix recovery with structural incoherence for robust face recognition
Chih-Fan Chen;Chia-Po Wei;Yu-Chiang Frank Wang.
computer vision and pattern recognition (2012)
Self-Learning Based Image Decomposition With Applications to Single Image Denoising
De-An Huang;Li-Wei Kang;Yu-Chiang Frank Wang;Chia-Wen Lin.
IEEE Transactions on Multimedia (2014)
Anomaly Detection via Online Oversampling Principal Component Analysis
Yuh-Jye Lee;Yi-Ren Yeh;Yu-Chiang Frank Wang.
IEEE Transactions on Knowledge and Data Engineering (2013)
Exploring Visual and Motion Saliency for Automatic Video Object Extraction
Wei-Te Li;Haw-Shiuan Chang;Kuo-Chin Lien;Hui-Tang Chang.
IEEE Transactions on Image Processing (2013)
Multi-label Zero-Shot Learning with Structured Knowledge Graphs
Chung-Wei Lee;Wei Fang;Chih-Kuan Yeh;Yu-Chiang Frank Wang.
computer vision and pattern recognition (2018)
Learning Deep Latent Space for Multi-Label Classification
Chih-Kuan Yeh;Wei-Chieh Wu;Wei-Jen Ko;Yu-Chiang Frank Wang.
national conference on artificial intelligence (2017)
Coupled Dictionary and Feature Space Learning with Applications to Cross-Domain Image Synthesis and Recognition
De-An Huang;Yu-Chiang Frank Wang.
international conference on computer vision (2013)
System and method for decentralized title recordation and authentication
Sean Moss-Pultz;Casey Alt;Christopher Hall;Le Quy Quoc Cuong.
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