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Artificial Intelligence in Data and Big Data Processing: Proceedings of ICABDE 2021 2022 ed. [Kietas viršelis]

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  • Formatas: Hardback, 735 pages, aukštis x plotis: 235x155 mm, weight: 1322 g, 253 Illustrations, color; 74 Illustrations, black and white; XXXIX, 735 p. 327 illus., 253 illus. in color., 1 Hardback
  • Serija: Lecture Notes on Data Engineering and Communications Technologies 124
  • Išleidimo metai: 19-May-2022
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030976092
  • ISBN-13: 9783030976095
Kitos knygos pagal šią temą:
Artificial Intelligence in Data and Big Data Processing: Proceedings of ICABDE 2021 2022 ed.Didesnis paveikslėlis
  • Formatas: Hardback, 735 pages, aukštis x plotis: 235x155 mm, weight: 1322 g, 253 Illustrations, color; 74 Illustrations, black and white; XXXIX, 735 p. 327 illus., 253 illus. in color., 1 Hardback
  • Serija: Lecture Notes on Data Engineering and Communications Technologies 124
  • Išleidimo metai: 19-May-2022
  • Leidėjas: Springer Nature Switzerland AG
  • ISBN-10: 3030976092
  • ISBN-13: 9783030976095
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9783030976095.html
Raktažodžiai:

The book presents studies related to artificial intelligence (AI) and its applications to process and analyze data and big data to create machines or software that can better understand business behavior, industry activities, and human health. The studies were presented at “The 2021 International Conference on Artificial Intelligence and Big Data in Digital Era” (ICABDE 2021), which was held in Ho Chi Minh City, Vietnam, during December 18-19, 2021.

The studies are pointing toward the famous slogan in technology “Make everything smarter,” i.e., creating machines that can understand and can communicate with humans, and they must act like humans in different aspects such as vision, communication, thinking, feeling, and acting.

“A computer would deserve to be called intelligent if it could deceive a human into believing that it was human”

—Alan Turing

Conceptual Graphs Clustering with Evolutionary Algorithms.- An Updated
IoU Loss Function for Bounding Box Regression.- Exhaustive Search for
Weighted Ensemble Classiers to Improve Performances on Imbalanced Dataset.-
Automatic Generation of Course Schedules Using Genetic Algorithm.-
Integrating Nom Language Model into Nom Optical Character Recognition.-
Calib-StyleSpeech: A Zero-Shot Approach in Voice Cloning of High Adaptive
Text to Speech System with Imbalanced Dataset.- Providing Syntactic Awareness
to Neural Machine Translation by Graph-Based Transformer.- Vietnamese Text
Summarization Based on Neural Network Models.- Adapting Cross-lingual Model
to Improve Vietnamese Dependency Parsing.- An Enhanced Ant Colony Algorithm
for Vehicle Path Planning Optimization Problem.