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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) 1st ed. 2021 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 857 pages, height x width: 235x155 mm, weight: 1324 g, 241 Illustrations, color; 105 Illustrations, black and white; XX, 857 p. 346 illus., 241 illus. in color., 1 Paperback / softback
  • Sērija : Advances in Intelligent Systems and Computing 1377
  • Izdošanas datums: 29-May-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030763455
  • ISBN-13: 9783030763459
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Proceedings of the International Conference on Artificial Intelligence and Computer Vision (AICV2021) 1st ed. 2021Palielināt
  • Formāts: Paperback / softback, 857 pages, height x width: 235x155 mm, weight: 1324 g, 241 Illustrations, color; 105 Illustrations, black and white; XX, 857 p. 346 illus., 241 illus. in color., 1 Paperback / softback
  • Sērija : Advances in Intelligent Systems and Computing 1377
  • Izdošanas datums: 29-May-2021
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030763455
  • ISBN-13: 9783030763459
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030763459.html
This book presents the 2nd International Conference on Artificial Intelligence and Computer Visions (AICV 2021) proceeding, which took place in Settat, Morocco, from June 28- to 30, 2021. AICV 2021 is organized by the Scientific Research Group in Egypt (SRGE) and the Computer, Networks, Mobility and Modeling Laboratory (IR2M), Hassan 1st University, Faculty of Sciences Techniques, Settat, Morocco.  This international conference highlighted essential research and developments in the fields of artificial intelligence and computer visions. The book is divided into sections, covering the following topics: Deep Learning and Applications; Smart Grid, Internet of Things, and Mobil Applications; Machine Learning and Metaheuristics Optimization; Business Intelligence and Applications; Machine Vision, Robotics, and Speech Recognition; Advanced Machine Learning Technologies; Big Data, Digital Transformation,  AI and Network Analysis; Cybersecurity; Feature Selection, Classification, and Applications. 

 

 
COVID-19 X-rays Model Detection Using Convolution Neural Network.- Deep
Learning Models Using Auxiliary Classifier GAN for Covid-19 Detection a
Comparative Study.- Feature Pyramid Network for COVID-19 Pneumonia Detection
from Chest X-rays Images.- Explore the Relationship Between COVID-19 Testing
Rates with the Number of Cases.- Deep Learning Method for Bone Abnormality
Detection Using Multi-view X-rays.- A Deep Autoencoder based Multi-Criteria
Recommender System.- Review on Supervised and Unsupervised Deep Learning
Techniques for Hyperspectral Images Classification.- The Impact of COVID-19
on E-learning: Advantages and Challenges.- Commodity Image Retrieval Based on
Convolutional Neural Network and Late Fusion.- Convolutional Neural Network
for Fire Video Image Detection in the Thermal Power Plant.