ICDSMLA 2020 de Amit Kumar

ICDSMLA 2020: Lecture Notes in Electrical Engineering, cartea 783

Editat de Amit Kumar, Sabrina Senatore, Vinit Kumar Gunjan

en Limba Engleză Paperback – 10 noi 2022

Spre deosebire de documentația tehnică standard sau manualele teoretice, Icdsmla 2020 oferă o perspectivă aplicată și experimentală asupra modului în care algoritmii de inteligență artificială interacționează cu problemele din lumea reală. Observăm o tranziție clară de la arhitecturile abstracte la implementări specifice, cum ar fi utilizarea RESNET-50 pentru diagnosticarea retinopatiei diabetice sau optimizarea debitului în rețelele de senzori wireless eterogene. Această abordare transformă volumul într-un depozit de soluții testate, nu doar un set de principii de programare.

Structura volumului este organizată în jurul unor studii de caz care indică o progresie de la procesarea de bază a datelor la modele complexe de deep learning. De exemplu, cuprinsul evidențiază algoritmi hibrizi GA-ACO pentru problema comis-voiajorului și modele de entropie aplicate cubului Rubik. Cititorul care a aplicat ideile din Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing va găsi aici o continuare firească, mutând accentul de pe infrastructura cloud pe rafinarea algoritmilor de clasificare, cum este modelul Modified Lazy Random Forest.

Apreciem rigoarea tehnică adusă de editori precum Vinit Kumar Gunjan, a cărui experiență în Advances in Cognitive Science and Communications se reflectă în selecția articolelor care pun accent pe interacțiunea om-calculator. Față de lucrările sale anterioare despre managementul deșeurilor, acest volum semnat pentru Springer consolidează expertiza autorului în zona de procesare a informației și sisteme inteligente, oferind o resursă masivă de peste 1300 de pagini pentru cercetătorii care au nevoie de date experimentale validate.

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Specificații

ISBN-13: 9789811636929
ISBN-10: 9811636923
Pagini: 1716
Ilustrații: XX, 1671 p. 986 illus., 741 illus. in color. In 2 volumes, not available separately.
Dimensiuni: 155 x 235 x 92 mm
Greutate: 2.55 kg
Ediția:1st ed. 2022
Editura: Springer
Colecția Lecture Notes in Electrical Engineering
Seria Lecture Notes in Electrical Engineering

Locul publicării:Singapore, Singapore

De ce să citești această carte

Recomandăm această lucrare profesioniștilor și cercetătorilor care caută implementări concrete de Machine Learning în domenii diverse, de la medicină la logistică. Cititorul câștigă acces la metodologii specifice de optimizare a algoritmilor și la rezultate experimentale care pot servi drept benchmark pentru propriile proiecte de dezvoltare software sau cercetare academică în domeniul inteligenței artificiale.

Despre autor

Vinit Kumar Gunjan este un cercetător și editor activ în comunitatea științifică internațională, fiind implicat în coordonarea unor volume de referință pentru Springer. Expertiza sa acoperă o gamă largă de domenii tehnice, de la științe cognitive și comunicare până la sustenabilitate. În lucrări precum Advances in Cognitive Science and Communications, acesta explorează intersecția dintre tehnologie și comportamentul uman, o temă recurentă și în Icdsmla 2020. Munca sa editorială se concentrează pe facilitarea schimbului de cunoștințe între mediul academic și industrie, promovând soluții bazate pe date pentru provocări contemporane complexe.

Descriere scurtă

This book gathers selected high-impact articles from the 2nd International Conference on Data Science, Machine Learning & Applications 2020. It highlights the latest developments in the areas of artificial intelligence, machine learning, soft computing, human–computer interaction and various data science and machine learning applications. It brings together scientists and researchers from different universities and industries around the world to showcase a broad range of perspectives, practices and technical expertise.

Cuprins

Automatic Notes Generation From Lecture Videos.- Correlation between Code Smells for Open Source Java Projects.- Throughput Improvement in Energy Efficient Heterogeneous Wireless Sensor Network.- Deep Learning Models for Rubik’s cube with Entropy Modelling.- Detecting Diabetic Retinopathy Using Deep Learning Technique with RESNET-50.- Restoration of Rician Corrupted MR Data using Improved Hybrid Model.- Flight Delay Prediction using Random Forest Classifier.- A framework using Markov-Baye’s model for Intrusion Detection in Wireless Sensor Network.- Effective text comment classification using Novel ML algorithm - Modified Lazy Random Forest.- Unraveling Deep Learning Performance in Cross-Sensor Iris Recognition.- Travelling Salesman Problem Using GA-ACO Hybrid Approach: A Review.- Efficient and Robust Indian Number Plate Recognition through Modified and Tuned LPRNet.- An Improved Machine Learning Prediction Model for Diabetes.

Notă biografică

Amit Kumar is passionate Forensic Scientist, Entrepreneur, Engineer, Bioinformatician and an IEEE Volunteer. In 2005, he founded first Private DNA Testing Company BioAxis DNA Research Centre (P) Ltd in Hyderabad, India, with an US Collaborator. He has vast experience of training 1000+ crime investigation officers and helped 750+ criminal and non-criminal cases to reach justice by offering analytical services in his laboratory. His group also works extensively on genetic predisposition risk studies of cancers and has been helping many cancer patients from 2012 to fight and win the battle against cancer. Amit is Member of IEEE Strategy Development and Environmental Assessment committee (SDEA) of IEEEMGA. He is Senior Member of IEEE and has been a very active IEEE Volunteer. With experience at Section, Council, Region and IEEE MGA levels in several capacities, he has driven a number of IEEE conferences, conference leadership programs, entrepreneurship development workshops and innovation and internship-related training. He is the Series Editor of Springer Briefs on Forensic and Medical Bioinformatics (FMB).

Sabrina Senatore received M.S. degree in computer science from University of Salerno, Italy, in 1999 and the Ph.D. in computer science from University of Salerno, in 2004. From 2005, she is Member at the University of Salerno. Her current position is Associate Professor of Computer Science at the University of Salerno, Italy. She is Chair of IEEE CIS Task Force on Intelligent Agents (TFIA) and Member of the IEEE CIS Intelligence Society Task Force: Fuzzy Systems for Web Intelligence; she is Associate Editor of Information Science, Elsevier, and she is also Editorial Board Member of the Applied Intelligence Journal and International Journal of Computational Intelligence Theory and Practice. Her current research interests include the development and application of intelligent systems based on the combination of techniques from soft computing, computational intelligence, text mining, information retrieval, semantic Web and intelligent agents and areas in which she has published extensively.

Vinit Kumar Gunjan is Associate Professor in Department of Computer Science & Engineering at CMR Institute of Technology Hyderabad (Affiliated to Jawaharlal Nehru Technological University, Hyderabad). He is Active Researcher, published research papers in IEEE, Elsevier & Springer Conferences, authored several books and edited volumes of Springer series, most of which are indexed in SCOPUS database. He was awarded with the prestigious Early Career Research Award in the year 2016 by Science Engineering Research Board, Department of Science & Technology Government of India. He is also Senior Member of IEEE and Active Volunteer of IEEE Hyderabad section; he volunteered in the capacity of Treasurer, Secretary and Chairman of IEEE Young Professionals Affinity Group & IEEE Computer Society and was involved as Organizer in many technical and non-technical workshops, seminars and conferences of IEEE & Springer.

Caracteristici

Highlights recent advances in artificial intelligence, machine learning, soft computing Discusses the applications of new emerging technologies for professionals and researchers alike Includes selected articles from the 2nd International Conference on Data Science & Machine Learning 2020