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Einband grossIntelligent Systems and Applications in Computer Vision
ISBN/GTIN

Intelligent Systems and Applications in Computer Vision

E-BookPDF0 - No protectionE-Book
342 Seiten
Englisch
Taylor & Franciserschienen am02.11.20231. Auflage
The book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection.mehr
Verfügbare Formate
BuchGebunden
EUR192,50
E-BookPDF0 - No protectionE-Book
EUR67,49
E-BookEPUB0 - No protectionE-Book
EUR67,49

Produkt

KlappentextThe book comprehensively covers a wide range of evolutionary computer vision methods and applications, feature selection and extraction for training and classification, and metaheuristic algorithms in image processing. It further discusses optimized image segmentation, its analysis, pattern recognition, and object detection.
Details
Weitere ISBN/GTIN9781000985801
ProduktartE-Book
EinbandartE-Book
FormatPDF
Format Hinweis0 - No protection
Erscheinungsjahr2023
Erscheinungsdatum02.11.2023
Auflage1. Auflage
Seiten342 Seiten
SpracheEnglisch
Dateigrösse43271 Kbytes
Illustrationen36 schwarz-weiße und 147 farbige Abbildungen, 47 schwarz-weiße Fotos, 136 schwarz-weiße Zeichnungen, 46 schwarz-weiße Tabellen
Artikel-Nr.11675567
Rubriken
Genre9200

Inhalt/Kritik

Inhaltsverzeichnis
Chapter 1
A Review Approach on Deep Learning Algorithms in Computer Vision

Chapter 2
Object Extraction from Real Time Color Images Using Edge Based Approach

Chapter 3
Deep Learning Techniques for Image Captioning

Chapter 4
Deep Learning Based Object Detection for Computer Vision Tasks: A Survey of Methods & Applications

Chapter 5
Deep Learning Algorithms for Computer Vision: A Deep Insight into Principles and Applications

Chapter 6
Handwritten Equation Solver Using Convolutional Neural Network

Chapter 7
Agriware: Crop Suggester System by Estimating the Soil Nutrient Indicators

Chapter 8
A Machine Learning Based Expeditious Covid-19 Prediction Model Through Clinical Blood Investigations

Chapter 9
Comparison of Image Based and Audio Based Techniques for Bird-Species Identification

Chapter 10
Detection of Ichthyosis Vulgaris Using SVM

Chapter 11
Chest X-Ray Diagnosis and Report Generation: Deep Learning Approach

Chapter 12
Deep Learning Based Automatic Image Caption Generation for Visually Impaired People

Chapter 13
Empirical Analysis of Machine Learning Techniques Under Class Imbalance and Incomplete Datasets

Chapter 14
Gabor Filter As Feature Extractor in Anomaly Detection from Radiology Images

Chapter 15
Discriminative Features Selection from Zernike Moments for Shape Based Image Retrieval System

Chapter 16
Corrected Components of Zernike Moments for Improved Content Based Image Retrieval: A Comprehensive Study

Chapter 17
Translate And Recreate Text in An Image

Chapter 18
Multi-Label Indian Scene Text Language Identification: Benchmark Dataset and Deep Ensemble Baseline

Chapter 19
AI Based Wearables for Healthcare Applications: A Survey of Smart Watches

Chapter 20
Nature Inspired Computing for Optimization

Chapter 21
Automated Smart Billing Cart for Fruits
mehr

Autor

Dr. Amit Kant Pandit is working as an Associate Professor and is Ex-Hod, DECE, in Shri Mata Vaishno Devi University (SMVDU), Katra (India). He is a Senior member of IEEE and MIR labs member and has 19 years of academic experience.

Mohamed Abouhawwash received the BSc and MSc degrees in statistics and computer science from Mansoura University, Mansoura, Egypt, in 2005 and 2011, respectively. He finished his Ph.D. in Statistics and Computer Science, 2015, in a channel program between Michigan State University, USA, and Mansoura University, Egypt. He is at Computational Mathematics, Science, and Engineering (CMSE), Biomedical Engineering (BME) and Radiology, Institute for Quantitative Health Science & Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA. He is an Assistant Professor with the Department of Mathematics, Faculty of Science, Mansoura University, Egypt. In 2018, Dr. Abouhawwash is a Visiting Scholar with the Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, Canada. His current research interests include evolutionary algorithms, machine learning, image reconstruction, and mathematical optimization. Dr. Abouhawwash was a recipient of the best master's and Ph.D. thesis awards from Mansoura University in 2012 and 2018, respectively.

Dr. Shubham Mahajan (Member, IEEE, ACM) received the B.Tech. degree from Baba Ghulam Shah Badshah University, the M.Tech. degree from Chandigarh University and Ph.D. degree with Shri Mata Vaishno Devi University (SMVDU), Katra, India. He is working as a Assistant Professor with Ajeenkya D Y Patil University, Pune. He has eight Indian, one Australian, one German Patent to his credit in the area of artificial intelligence and image processing. He has authored/coauthored more than 50 publications including peer-reviewed journals and conferences. His main research interests include image processing, video compression, image segmentation, fuzzy entropy, nature-inspired computing methods with applications in optimization, data mining, machine learning, robotics, and optical communication, and also received the 'Best Research Paper Award' from ICRIC 2019 (Springer, LNEE) and also received the Best Student Award-2019, IEEE Region-10 Travel Grant Award-2019, 2nd runner up prize in IEEE RAS HACKATHON-2019 (Bangladesh) and IEEE Student Early Researcher Conference Fund (SERCF-2020), Emerging Scientist Award-2021, and IEEE Signal Processing Society Professional Development Grant-2021. He was a Campus Ambassador for IEEE, IIT Bombay, Kanpur, Varanasi, Delhi and various MNC's. He is constantly looking for collaboration opportunities with foreign professors and students.