Tin Kam Ho (Chinese :何天琴) is a computer scientist at IBM Research with contributions to machine learning, data mining, and classification. Ho is noted for introducing random decision forests in 1995, and for her pioneering work in ensemble learning and data complexity analysis. She is an IEEE fellow and IAPR fellow.
Ho completed her undergraduate education at the Chinese University of Hong Kong in 1984. She received a Ph.D. in computer science from State University of New York at Buffalo in 1992.
She led the Statistics and Learning Research Department of Bell Labs at Murray Hill, NJ. In 1995, she published the article Random decision forests,which became the foundation of the random forest method commonly used by later data scientists.
Ho also pioneered research in multiple classifier systems, ensemble learning, and data complexity analysis,and pursued applications of automatic learning in reading systems and many areas of science and engineering. She also led major efforts on modeling and monitoring large-scale optical transmission systems. Later she worked on wireless geo-location, video surveillance, smart grid data mining, user profiling, customer experience modeling, and analysis of diagnostic processes.
Since 2014, Ho has been a research scientist in artificial intelligence at IBM. She worked on semantic analysis in natural language processing, contributing to machine learning, data mining, and classification methods at IBM Watson and Watson Health. Thereafter she turned to generative AI applications at IBM Research.
Her contributions were recognized by a Bell Labs President's Gold Award and two Bell Labs Teamwork Awards, a Young Scientist Award from ICDAR in 1999, and the 2008 Pierre Devijver Award for Statistical Pattern Recognition.She served as Editor-in-chief of the journal Pattern Recognition Letters in 2004-2010, and in earlier years as Associate Editor for PAMI, Pattern Recognition, Editor for Int. J. on Document Analysis and Recognition, as well as guest editors for other publications.
Ho was elected an IEEE fellow in 2006, and is also an IAPR fellow.
Handwriting recognition (HWR), also known as handwritten text recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. The image of the written text may be sensed "off line" from a piece of paper by optical scanning or intelligent word recognition. Alternatively, the movements of the pen tip may be sensed "on line", for example by a pen-based computer screen surface, a generally easier task as there are more clues available. A handwriting recognition system handles formatting, performs correct segmentation into characters, and finds the most possible words.
Thomas Shi-Tao Huang was a Chinese-born American computer scientist, electrical engineer, and writer. He was a researcher and professor emeritus at the University of Illinois at Urbana-Champaign (UIUC). Huang was one of the leading figures in computer vision, pattern recognition and human computer interaction.
King-Sun Fu was a Chinese-born American computer scientist. He was a Goss Distinguished Professor at Purdue University School of Electrical and Computer Engineering in West Lafayette, Indiana. He was instrumental in the founding of International Association for Pattern Recognition (IAPR), served as its first president, and is widely recognized for his extensive and pioneering contributions to the field of pattern recognition and machine intelligence. In honor of the memory of Professor King-Sun Fu, IAPR gives the biennial King-Sun Fu Prize to a living person in the recognition of an outstanding technical contribution to the field of pattern recognition. The first King-Sun Fu Prize was presented in 1988, to Azriel Rosenfeld.
In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from any of the constituent learning algorithms alone. Unlike a statistical ensemble in statistical mechanics, which is usually infinite, a machine learning ensemble consists of only a concrete finite set of alternative models, but typically allows for much more flexible structure to exist among those alternatives.
Léon Bottou is a researcher best known for his work in machine learning and data compression. His work presents stochastic gradient descent as a fundamental learning algorithm. He is also one of the main creators of the DjVu image compression technology, and the maintainer of DjVuLibre, the open source implementation of DjVu. He is the original developer of the Lush programming language.
Sargur Narasimhamurthy Srihari was an Indian and American computer scientist and educator who made contributions to the field of pattern recognition. The principal impact of his work has been in handwritten address reading systems and in computer forensics. He was a SUNY Distinguished Professor in the School of Engineering and Applied Sciences at the University at Buffalo, Buffalo, New York, USA.
In machine learning the random subspace method, also called attribute bagging or feature bagging, is an ensemble learning method that attempts to reduce the correlation between estimators in an ensemble by training them on random samples of features instead of the entire feature set.
Matti Kalevi Pietikäinen is a computer scientist. He is currently Professor (emer.) in the Center for Machine Vision and Signal Analysis, University of Oulu, Finland. His research interests are in texture-based computer vision, face analysis, affective computing, biometrics, and vision-based perceptual interfaces. He was Director of the Center for Machine Vision Research, and Scientific Director of Infotech Oulu.
The MNIST database is a large database of handwritten digits that is commonly used for training various image processing systems. The database is also widely used for training and testing in the field of machine learning. It was created by "re-mixing" the samples from NIST's original datasets. The creators felt that since NIST's training dataset was taken from American Census Bureau employees, while the testing dataset was taken from American high school students, it was not well-suited for machine learning experiments. Furthermore, the black and white images from NIST were normalized to fit into a 28x28 pixel bounding box and anti-aliased, which introduced grayscale levels.
Anil Kumar Jain is an Indian-American computer scientist and University Distinguished Professor in the Department of Computer Science & Engineering at Michigan State University, known for his contributions in the fields of pattern recognition, computer vision and biometric recognition. He is among the top few most highly cited researchers in computer science and has received various high honors and recognitions from institutions such as ACM, IEEE, AAAS, IAPR, SPIE, the U.S. National Academy of Engineering, the Indian National Academy of Engineering and the Chinese Academy of Sciences.
Josef KittlerFREng is a British scientist and Distinguished Professor at University of Surrey, specialising in pattern recognition and machine intelligence.
Venu Govindaraju is an Indian-American whose research interests are in the fields of document image analysis and biometrics. He presently serves as the Vice President for Research and Economic Development. He is a SUNY Distinguished Professor of Computer Science and Engineering, School of Engineering and Applied Sciences at the University at Buffalo, The State University of New York, Buffalo, NY, USA.
Theodosios Pavlidis is a computer scientist and Distinguished Professor Emeritus of Computer Science at the State University of New York, Stony Brook.
Jianying Hu is a Chinese-American computer scientist at the IBM Thomas J. Watson Research Center, Yorktown Heights, NY, USA, known for her work in data mining, machine learning, artificial intelligence and health informatics. She is an IBM Fellow, Global Science Leader of AI for Healthcare and Director of Healthcare and Life Sciences Research at IBM. She is also an Adjunct Professor in the Department of Medicine at the Icahn School of Medicine at Mount Sinai. She has published over 150 scientific papers and holds more than 50 patents.
René Vidal is a Chilean electrical engineer and computer scientist who is known for his research in machine learning, computer vision, medical image computing, robotics, and control theory. He is the Herschel L. Seder Professor of the Johns Hopkins Department of Biomedical Engineering, and the founding director of the Mathematical Institute for Data Science (MINDS).
Scene text is text that appears in an image captured by a camera in an outdoor environment.
Gang Hua is a Chinese-American computer scientist who specializes in the field of computer vision and pattern recognition. He is an IEEE Fellow, IAPR Fellow and ACM Distinguished Scientist. He is a key contributor to Microsoft's Facial Recognition technologies.
Josiane Zerubia is a French research scientist. She is the Director of Research at INRIA (DRCE), Université Côte d'Azur. Dr. Zerubia has made pioneering research contributions. She has been the Principal Investigator of numerous projects like of the Ayin (2012-2016), the Ariana (1998-2011) and of the Pastis (1995-1997). Presently, she is leading as head of the Ayana exploratory project (2020-2023). She has been professor (PR1) at SUPAERO (ISAE) in Toulouse since 1999.
Ludmila (Lucy) Ilieva Kuncheva is a Bulgarian-British computer scientist known for her research on pattern recognition and machine learning, and particularly on systems that combine results from multiple classifiers. She is professor in computer science at Bangor University in Wales.
Mário A. T. Figueiredo is a Portuguese engineer, academic, and researcher. He is an IST Distinguished Professor and holds the Feedzai chair of machine learning at IST, University of Lisbon.