Soft Computing for Problem Solving : Proceedings of the SocProS 2022 / edited by Manoj Thakur, Samar Agnihotri, Bharat Singh Rajpurohit, Millie Pant, Kusum Deep, Atulya K. Nagar.

Format:

Book

Contributor:

Thakur, Manoj, editor.

Series:

Lecture Notes in Networks and Systems, 2367-3389 ; 547

Language:

English

Subjects (All):

Computational intelligence.

Artificial intelligence.

Algorithms.

Computational Intelligence.

Artificial Intelligence.

Local Subjects:

Computational Intelligence.

Artificial Intelligence.

Algorithms.

Physical Description:

1 online resource (727 pages)

Edition:

1st ed. 2023.

Place of Publication:

Singapore : Springer Nature Singapore : Imprint: Springer, 2023.

Summary:

This book provides an insight into the 11th International Conference on Soft Computing for Problem Solving (SocProS 2022). This international conference is a joint technical collaboration of the Soft Computing Research Society and the Indian Institute of Technology Mandi. This book presents the latest achievements and innovations in the interdisciplinary areas of Soft Computing, Machine Learning, and Data Science. It brings together the researchers, engineers, and practitioners to discuss thought-provoking developments and challenges, in order to select potential future directions. It covers original research papers in the areas including but not limited to algorithms (artificial neural network, deep learning, statistical methods, genetic algorithm, and particle swarm optimization) and applications (data mining and clustering, computer vision, medical and healthcare, finance, data envelopment analysis, business, and forecasting applications). This book is beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.

Contents:

Chapter 1. Benchmarking state-of-the-art methodologies for optic disc segmentation

Chapter 2. Automated Student Emotion Analysis During Online Classes using Convolutional Neural Network

Chapter 3. Transfer Learning based Malware Classification

Chapter 4. A Study on Metric-Based and Initialization-Based Methods for Few-Shot Image Classification

Chapter 5. A Fast and Efficient Methods for Eye pre-processing and DR Level Detection

Chapter 6. A deep neural model CNN-LSTM network for automated sleep staging based on a single-channel EEG signal

Chapter 7. An Ensemble Model for Gait Classification in Children and Adolescent with Cerebral Palsy: A Low-Cost Approach

Chapter 8. Imbalanced Learning of Regular Grammar for DFA Extraction from LSTM Architecture

Chapter 9. Medical Prescription Label Reading using Computer Vision and Deep Learning

Chapter 10. Autoencoder-based Deep Neural Architecture for Epileptic Seizures Classification

Chapter 11. Stock Market Prediction using Deep Learning Techniques for Short and Long Horizon

Chapter 12. Improved CNN Model for Breast Cancer Classification

Chapter 13. Performance Assessment of Normalization in CNN with Retinal Image Segmentation

Chapter 14. A novel multi-day ahead index price forecast using multi-output based deep learning system

Chapter 15. Automatic Retinal Vessel Segmentation using BTLBO. etc.

Notes:

Includes bibliographical references and index.

Other Format:

Print version: Thakur, Manoj Soft Computing for Problem Solving

ISBN:

981-19-6525-0