Optimum-Path Forest: Theory, Algorithms, and Applications

Alexandre Xavier Falcao · João Paulo Papa

ene 2022 · Academic Press

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The Optimum-Path Forest (OPF) classifier was first published in 2008 in its supervised and unsupervised versions with applications in medicine and image classification. Since then, it has expanded to a variety of other applications such as remote sensing, electrical and petroleum engineering, and biology. In recent years, multi-label and semi-supervised versions were also developed to handle video classification problems. The book presents the principles, algorithms and applications of Optimum-Path Forest, giving the theory and state-of-the-art as well as insights into future directions. - Presents the first book on Optimum-path Forest - Shows how it can be used with Deep Learning - Gives a wide range of applications - Includes the methods, underlying theory and applications of Optimum-Path Forest (OPF)

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Alexandre Xavier Falcao is a full professor atthe Institute of Computing (IC), University of Campinas (Unicamp),where he has worked since 1998. He attended the Federal University of Pernambuco from 1984-1988, where he got a B.Sc. in Electrical Engineering. He then attended Unicamp, where he got an M.Sc. (1993), and a Ph.D. (1996), in Electrical Engineering, by working on volumetric data visualization and medicalimage segmentation. During his Ph.D., he worked with the Medical Image Processing Group at the University of Pennsylvania from 1994-1996. In 2011-2012, he spent a one-year sabbatical at the Robert W. Holley Center for Agriculture and Health (USDA, Cornell University), working on image analysis applied to plant biology. He served as Associate Director of IC-Unicamp (2006-2007), Coordinator of its Post-Graduation Program (2009-2011), and Senior Area Editor of IEEE Signal Processing Letters (2016-2020). He is currently a top level research fellow at the for the Brazilian National Council for Scientific and Technological Development (CNPq), President of the Special Commission of Computer Graphics and Image Processing (CEGRAPI) for the Brazilian Computer Society (SBC), and Area Coordinator of Computer Science for the Sao Paulo Research Foundation (FAPESP). Among the several awards he received over the years, it is worth mentioning three Unicamp inventor awards at the category "License Technology" (2011, 2012, and 2020), three awards of academic excellence (2006, 2011, 2016) from IC-Unicamp, one award of academic recognition "Zeferino Vaz" from Unicamp (2014), and the best paper award in the year of 2012 from the journal Pattern Recognition (received at Stockholm, Sweden, during theconference ICPR 2014). His research work aims at computational models to learn and interpretthe semantic content of images in the domain of several applications. The areas of interest include image and videoprocessing, data visualization, medical image analysis, remote sensing, graph algorithms, image annotation, organization, and retrieval, and (interactive) machine learning and pattern recognition.

Joao Paulo Papa obtained his Ph.D. in Computer Science from University of Campinas, Brazil, in 2008, and was a visiting scholar at Harvard University from 2014-2015. He has been a Professor at Sao Paulo State University (UNESP), Brazil, since 2009, and his main interests include image processing, machine learning and meta-heuristic optimization.