Prof. KC Santosh is the Chair of the Department of Computer Science at the University of South Dakota (USD). Before joining USD, Prof. Santoshworked as a research fellow at the U.S. National Library of Medicine (NLM), National Institutes of Health (NIH). He was a postdoctoral research scientist at the LORIA research centre (with industrial partner, ITESOFT (France)). He has demonstrated expertise in artificial intelligence, machine learning, pattern recognition, computer vision, image processing and data mining with applications, such as medical imaging informatics, document imaging, biometrics, forensics, and speech analysis. His research projects are funded bymultiple agencies, such as SDCRGP, Department of Education, National Science Foundation, and Asian Office of Aerospace Research and Development. He is the proud recipient of the Cutler Award for Teaching and Research Excellence (USD, 2021), the President’s Research Excellence Award (USD, 2019), and the Ignite Award from the U.S. Department
Télécharger le livre :  Advances in Artificial-Business Analytics and Quantum Machine Learning

The book presents select proceedings of the 3rd International Conference on “Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects” (Com-IT-Con 2023) held at the Manav Rachna University in July 2023. It covers the topics such...
Editeur : Springer
Parution : 2024-10-18
Collection : Lecture Notes in Networks and Systems
Format(s) : PDF, ePub
137,14

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Télécharger le livre :  Advances in Artificial-Business Analytics and Quantum Machine Learning

This book presents select proceedings of the 3rd International Conference on “Artificial-Business Analytics, Quantum and Machine Learning: Trends, Perspectives, and Prospects” (Com-IT-Con 2023) held at the Manav Rachna University in July 2023. It covers topics such as...
Editeur : Springer
Parution : 2024-09-18

Format(s) : PDF, ePub
168,79

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Télécharger le livre :  Active Learning to Minimize the Possible Risk of Future Epidemics

Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big...
Editeur : Springer
Parution : 2023-11-22
Collection : SpringerBriefs in Applied Sciences and Technology
Format(s) : PDF, ePub
47,46

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Télécharger le livre :  AI, Ethical Issues and Explainability—Applied Biometrics

AI has contributed a lot and biometrics is no exception. To makeAI solutions commercialized/fully functional, one requires trustworthy and explainableAI (XAI) solutions while respecting ethical issues. Within the scope of biometrics, the book aims at both revisiting...
Editeur : Springer
Parution : 2022-08-24
Collection : SpringerBriefs in Applied Sciences and Technology
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52,74

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Télécharger le livre :  Artificial Intelligence and Machine Learning in Public Healthcare

This book discusses and evaluates AI and machine learning (ML) algorithms in dealing with challenges that are primarily related to public health. It also helps find ways in which we can measure possible consequences and societal impacts by taking the following factors...
Editeur : Springer
Parution : 2022-01-01

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73,84

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