Prof. C.H. Chen received his Ph. D in electrical engineering from Purdue University West Lafayette, Indiana, in 1965, his MSEE from the University of Tennessee, Knoxville, in 1962, and his BSEE from the National Taiwan University, Taipei in 1959. He is currently the chancellor professor emeritus of electrical and computer engineering at the University of Massachusetts Dartmouth, where he has been a faculty member since 1968. His research areas encompass statistical pattern recognition and signal/image processing with applications to remote sensing, medical imaging, geophysical, underwater acoustics, and nondestructive testing problems, as well as computer vision for video surveillance, time-series analysis, and neural networks. He has edited and authored 37 books in his areas of research, including Digital Waveform Processing and Recognition (CRC Press 1982), Signal and Image Processing for Remote Sensing (CRC Press, first edition 2006, second edition 2012), and Compressive Sensing of Earth Observations (CRC Press 2017). He served as associate editor of the IEEE Transactions on Acoustic, Speech, and Signal Processing for 4 years, associate editor of the IEEE Transactions on Geoscience and Remote Sensing for 15 years, and since 2008 he has been a board member/associate editor of Pattern Recognition particularly on remote sensing topics. Dr. Chen has been a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) since 1988, a Life Fellow of the IEEE since 2003, and a Fellow of the International Association of Pattern Recognition (IAPR) since 1996. He is also the editor of the book series entitled Signal and Image Processing of Earth Observations, for CRC Press.

• PART I General TopicsChapter 1 A Brief Overview of 60 Years of Progress on Signal/Image Processing forRemote SensingC.H. ChenChapter 2 Proven Approaches of Using Innovative High‑Performance ComputingArchitectures in Remote SensingRocco Sedona, Gabriele Cavallaro, Morris Riedel, and Jon Atli BenediktssonPART II Signal Processing for Remote SensingChapter 3 Machine Learning Techniques for Geophysical Parameter RetrievalsAdam B. Milstein, Michael Pieper, and William J. BlackwellChapter 4 Subsurface Inverse Profiling and Imaging Using Stochastic Optimization TechniquesMaryam Hajebi and Ahmad HoorfarChapter 5 Close and Remote Ground Penetrating Radar Surveys via Microwave Tomography: State of Art and PerspectivesGianluca Gennarelli, Giuseppe Esposito, Giovanni Ludeno,Francesco Soldovieri, and Ilaria CatapanoChapter 6 Polarimetric SAR Signature of Complex Scene: A Simulation StudyKun‑Shan Chen, Cheng‑Yen Chiang, and Ying YangChapter 7 Machine Learning for Arctic Sea Ice Physical Properties Estimation Using Dual‑Polarimetric SAR DataKatalin Blix, Martine M. Espeseth, and Torbjorn EltoftChapter 8 Riemannian Clustering of PolSAR Data Using the Polar DecompositionMadalina Ciuca, Gabriel Vasile, Marco Congedo, and Michel GayChapter 9 Seismic Velocity Picking Using Hopfield Neural NetworkKou‑Yuan Huang and Jia‑Rong YangChapter 10 Expanded Radial Basis Function Network with Proof of Hidden Node Number by Recurrence Relation for Well Log Data InversionKou‑Yuan Huang, Liang‑Chi Shen, Jiun‑Der You, and Li‑Sheng WengPART III Image Processing for Remote SensingChapter 11 Convolutional Neural Networks Meet Markov Random Fields for Semantic Segmentation of Remote Sensing ImagesMartina Pastorino, Gabriele Moser, Sebastiano B. Serpico, and Josiane ZerubiaChapter 12 Deep Learning Methods for Satellite Image Super‑ResolutionDiego Valsesia and Enrico MagliChapter 13 Machine Learning in Remote SensingRonny HanschChapter 14 Robust Training of Deep Neural Networks with Weakly Labelled DataGianmarco Perantoni and Lorenzo BruzzoneChapter 15 Semantic Segmentation with OTBTF and KerasRemi CressonChapter 16 Performance of a Diffusion Model for Instance Segmentation in Remote Sensing ImagerySelin Koles, Sedat Ozer, and C.H. ChenChapter 17 Land Cover Classification Using Attention‑Based Multi‑Modal Image Fusion: An Explainable AnalysisOktay Karakus, Wanli Ma, and Paul L. RosinChapter 18 FPGA Compressive Sensing Method Applied to Hyperspectral ImageryJose Nascimento and Mario VestiasChapter 19 Large‑Scale Fine‑Grained Change Detection from Multisensory Satellite ImagesAndrea Garzelli and Claudia ZoppettiChapter 20 Change Detection on Graphs: Exploiting Graph Structure from Bi‑temporal Satellite ImageryJuan F. Florez‑Ospina, Hernan D. Benitez‑Restrepo, and David A. Jimenez‑SierraChapter 21 Target Detection in Hyperspectral Imaging Using Neural NetworksEdisanter Lo and Emmett Ientilucci

Prof. C.H. Chen received his Ph. D in electrical engineering from Purdue University West Lafayette, Indiana, in 1965, his MSEE from the University of Tennessee, Knoxville, in 1962, and his BSEE from the National Taiwan University, Taipei in 1959. He is currently the chancellor professor emeritus of electrical and computer engineering at the University of Massachusetts Dartmouth, where he has been a faculty member since 1968. His research areas encompass statistical pattern recognition and signal/image processing with applications to remote sensing, medical imaging, geophysical, underwater acoustics, and nondestructive testing problems, as well as computer vision for video surveillance, time-series analysis, and neural networks. He has edited and authored 37 books in his areas of research, including Digital Waveform Processing and Recognition (CRC Press 1982), Signal and Image Processing for Remote Sensing (CRC Press, first edition 2006, second edition 2012), and Compressive Sensing of Earth Observations (CRC Press 2017). He served as associate editor of the IEEE Transactions on Acoustic, Speech, and Signal Processing for 4 years, associate editor of the IEEE Transactions on Geoscience and Remote Sensing for 15 years, and since 2008 he has been a board member/associate editor of Pattern Recognition particularly on remote sensing topics. Dr. Chen has been a Fellow of the Institute of Electrical and Electronic Engineers (IEEE) since 1988, a Life Fellow of the IEEE since 2003, and a Fellow of the International Association of Pattern Recognition (IAPR) since 1996. He is also the editor of the book series entitled Signal and Image Processing of Earth Observations, for CRC Press.

• PART I General TopicsChapter 1 A Brief Overview of 60 Years of Progress on Signal/Image Processing forRemote SensingC.H. ChenChapter 2 Proven Approaches of Using Innovative High‑Performance ComputingArchitectures in Remote SensingRocco Sedona, Gabriele Cavallaro, Morris Riedel, and Jon Atli BenediktssonPART II Signal Processing for Remote SensingChapter 3 Machine Learning Techniques for Geophysical Parameter RetrievalsAdam B. Milstein, Michael Pieper, and William J. BlackwellChapter 4 Subsurface Inverse Profiling and Imaging Using Stochastic Optimization TechniquesMaryam Hajebi and Ahmad HoorfarChapter 5 Close and Remote Ground Penetrating Radar Surveys via Microwave Tomography: State of Art and PerspectivesGianluca Gennarelli, Giuseppe Esposito, Giovanni Ludeno,Francesco Soldovieri, and Ilaria CatapanoChapter 6 Polarimetric SAR Signature of Complex Scene: A Simulation StudyKun‑Shan Chen, Cheng‑Yen Chiang, and Ying YangChapter 7 Machine Learning for Arctic Sea Ice Physical Properties Estimation Using Dual‑Polarimetric SAR DataKatalin Blix, Martine M. Espeseth, and Torbjorn EltoftChapter 8 Riemannian Clustering of PolSAR Data Using the Polar DecompositionMadalina Ciuca, Gabriel Vasile, Marco Congedo, and Michel GayChapter 9 Seismic Velocity Picking Using Hopfield Neural NetworkKou‑Yuan Huang and Jia‑Rong YangChapter 10 Expanded Radial Basis Function Network with Proof of Hidden Node Number by Recurrence Relation for Well Log Data InversionKou‑Yuan Huang, Liang‑Chi Shen, Jiun‑Der You, and Li‑Sheng WengPART III Image Processing for Remote SensingChapter 11 Convolutional Neural Networks Meet Markov Random Fields for Semantic Segmentation of Remote Sensing ImagesMartina Pastorino, Gabriele Moser, Sebastiano B. Serpico, and Josiane ZerubiaChapter 12 Deep Learning Methods for Satellite Image Super‑ResolutionDiego Valsesia and Enrico MagliChapter 13 Machine Learning in Remote SensingRonny HanschChapter 14 Robust Training of Deep Neural Networks with Weakly Labelled DataGianmarco Perantoni and Lorenzo BruzzoneChapter 15 Semantic Segmentation with OTBTF and KerasRemi CressonChapter 16 Performance of a Diffusion Model for Instance Segmentation in Remote Sensing ImagerySelin Koles, Sedat Ozer, and C.H. ChenChapter 17 Land Cover Classification Using Attention‑Based Multi‑Modal Image Fusion: An Explainable AnalysisOktay Karakus, Wanli Ma, and Paul L. RosinChapter 18 FPGA Compressive Sensing Method Applied to Hyperspectral ImageryJose Nascimento and Mario VestiasChapter 19 Large‑Scale Fine‑Grained Change Detection from Multisensory Satellite ImagesAndrea Garzelli and Claudia ZoppettiChapter 20 Change Detection on Graphs: Exploiting Graph Structure from Bi‑temporal Satellite ImageryJuan F. Florez‑Ospina, Hernan D. Benitez‑Restrepo, and David A. Jimenez‑SierraChapter 21 Target Detection in Hyperspectral Imaging Using Neural NetworksEdisanter Lo and Emmett Ientilucci