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E-raamat: Intelligent Systems Design and Applications: Deep Learning, Volume 2

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Intelligent Systems Design and Applications: Deep Learning, Volume 2Suurem pilt
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This book highlights recent research on intelligent systems and nature-inspired computing. It presents 47 selected papers focused on Deep Learning from the 23rd International Conference on Intelligent Systems Design and Applications (ISDA 2023), which was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India, and in online mode. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. ISDA 2023 had contributions by authors from 64 countries. This book offers a valuable reference guide for all scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and deep learning.

Deep Learning Approach for Autonomous Spacecraft Landing.- Deep Learning
Approach for Flood Mapping Using Satellite Images Dataset.- Large Language
Models for Named Entity Recognition NER of Skills in Job Postings in German.-
Machine Learning Approaches for Investing Strategies in Stock Market.- OP
FedELM One pass Privacy-preserving Federated Classification via Evolving
Clustering Method and Extreme Learning Machine hybrid.- Gamma Corrected
Pyramid Pix2pix Breast Cancer HE to IHC Image Generation.- Unveiling
Deepfakes Customized Convolutional Neural Networks for Detection.- The Nasdaq
Composite Index Prediction Using LSTM and Bi LSTM Multivariate Deep Learning
Approaches.- PlastOcean Detecting Floating Marine Macro Litter FMML using
Deep Learning Models.- Data Augmentation Using Generative Neural Networks
Based on Fourier Feature Mapping.- Delay Risk Detection in Road Construction
Projects Utilizing Large Language Model.- Unlocking The Potential of Novel
LSTM in Airline Recommendation Prediction.- Pylung a supporting tool for
comparative study of ViT and CNN based models used for lung nodules
classification.- Deep Learning model for predicting rice plant disease
identification and classification for improving the yield.
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