His primary scientific interests are in Artificial intelligence, Pattern recognition, Computer vision, Pixel and Machine learning. His research on Artificial intelligence frequently connects to adjacent areas such as Natural language processing. Chew Lim Tan has researched Pattern recognition in several fields, including Text mining, Object detection and Sobel operator.
His work deals with themes such as Segmentation, Feature detection and Hausdorff distance, which intersect with Pixel. Chew Lim Tan has included themes like Data mining, Data set and Coreference in his Machine learning study. His biological study spans a wide range of topics, including Graphics and Pattern recognition.
Chew Lim Tan spends much of his time researching Artificial intelligence, Pattern recognition, Computer vision, Natural language processing and Feature extraction. Artificial intelligence is closely attributed to Machine learning in his research. His research integrates issues of Feature, Word, Cluster analysis, Contextual image classification and Histogram in his study of Pattern recognition.
His study in Image processing, Orientation, Image restoration, Edge detection and Image are all subfields of Computer vision. His work deals with themes such as Character, Speech recognition, Task and Information retrieval, which intersect with Natural language processing. His research in Pixel intersects with topics in Wavelet and Sobel operator.
Chew Lim Tan mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Pixel and Feature extraction. His work is connected to Image, Histogram, Segmentation, Orientation and Text segmentation, as a part of Artificial intelligence. Chew Lim Tan combines subjects such as Sobel operator and Graphics with his study of Pattern recognition.
His work on Wavelet as part of general Computer vision research is frequently linked to Line, bridging the gap between disciplines. Chew Lim Tan focuses mostly in the field of Pixel, narrowing it down to topics relating to Robustness and, in certain cases, Similarity, Spectral clustering, The Internet, Born-digital and Linkage. His study in Feature extraction is interdisciplinary in nature, drawing from both Delaunay triangulation, Categorization, Task and Keyword spotting.
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Computer vision, Pixel and Feature extraction. His Artificial intelligence research incorporates themes from Data mining and Graphics. His work carried out in the field of Pattern recognition brings together such families of science as Orientation and Histogram.
His Computer vision study combines topics from a wide range of disciplines, such as Neural coding and k-nearest neighbors algorithm. As part of the same scientific family, Chew Lim Tan usually focuses on Pixel, concentrating on Font and intersecting with Image resolution, Contrast and Text mining. The various areas that Chew Lim Tan examines in his Support vector machine study include Representation and Automatic image annotation.
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Discretization: An Enabling Technique
Huan Liu;Farhad Hussain;Chew Lim Tan;Manoranjan Dash.
Data Mining and Knowledge Discovery (2002)
Supervised and Traditional Term Weighting Methods for Automatic Text Categorization
Man Lan;Chew Lim Tan;Jian Su;Yue Lu.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)
A case study on using neural networks to perform technical forecasting of forex
Jingtao Yao;Chew Lim Tan.
A Laplacian Approach to Multi-Oriented Text Detection in Video
P Shivakumara;Trung Quy Phan;Chew Lim Tan.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2011)
Robust Document Image Binarization Technique for Degraded Document Images
Bolan Su;Shijian Lu;Chew Lim Tan.
IEEE Transactions on Image Processing (2013)
Binarization of historical document images using the local maximum and minimum
Bolan Su;Shijian Lu;Chew Lim Tan.
document analysis systems (2010)
Recognizing names in biomedical texts: a machine learning approach
Guodong Zhou;Jie Zhang;Jian Su;Dan Shen.
Document image binarization using background estimation and stroke edges
Shijian Lu;Bolan Su;Chew Lim Tan.
International Journal on Document Analysis and Recognition (2010)
A robust arbitrary text detection system for natural scene images
Anhar Risnumawan;Palaiahankote Shivakumara;Chee Seng Chan;Chew Lim Tan.
Expert Systems With Applications (2014)
Option price forecasting using neural networks
Jingtao Yao;Yili Li;Chew Lim Tan.
Omega-international Journal of Management Science (2000)
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