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    1. Data och IT
    2. Systemvetenskap och AI

    Integrating Metaheuristics in Computer Vision for Real-World Optimization Problems

    AvShubham Mahajan,Kapil Joshi

    Inbunden, Engelska, 2024

    2 134 kr

    Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

    Beskrivning

    A comprehensive book providing high-quality research addressing challenges in theoretical and application aspects of soft computing and machine learning in image processing and computer vision. Researchers are working to create new algorithms that combine the methods provided by CI approaches to solve the problems of image processing and computer vision such as image size, noise, illumination, and security. The 19 chapters in this book examine computational intelligence (CI) approaches as alternative solutions for automatic computer vision and image processing systems in a wide range of applications, using machine learning and soft computing. Applications highlighted in the book include: diagnostic and therapeutic techniques for ischemic stroke, object detection, tracking face detection and recognition;computational-based strategies for drug repositioning and improving performance with feature selection, extraction, and learning;methods capable of retrieving photometric and geometric transformed images;concepts of trading the cryptocurrency market based on smart price action strategies; comparative evaluation and prediction of exoplanets using machine learning methods; the risk of using failure rate with the help of MTTF and MTBF to calculate reliability; a detailed description of various techniques using edge detection algorithms;machine learning in smart houses; the strengths and limitations of swarm intelligence and computation; how to use bidirectional LSTM for heart arrhythmia detection;a comprehensive study of content-based image-retrieval techniques for feature extraction;machine learning approaches to understanding angiogenesis;handwritten image enhancement based on neutroscopic-fuzzy.Audience The book has been designed for researchers, engineers, graduate, and post-graduate students wanting to learn more about the theoretical and application aspects of soft computing and machine learning in image processing and computer vision.

    Produktinformation

    • Utgivningsdatum:2024-08-13
    • Mått:185 x 267 x 28 mm
    • Vikt:975 g
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:368
    • Förlag:John Wiley & Sons Inc
    • ISBN:9781394230921

    Utforska kategorier

    • Systemvetenskap och AI inom Data och IT

    Mer om författaren

    Shubham Mahajan, PhD, is an assistant professor in the School of Engineering at Ajeekya D Y Patil University, Pune, Maharashtra, India. He has eight Indian, one Australian, and one German patent to his credit in artificial intelligence and image processing. He has authored/co-authored 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. Kapil Joshi, PhD, is an assistant professor in the Computer Science & Engineering Department, Uttaranchal Institute of Technology in Dehradun, India. His doctorate was on image quality enhancement using fusion techniques. He has 8 years of academic experience and has published patents, research papers, and two books. In 2021, he was awarded the ‘Best Young Researcher’ Award in Global Education and Corporate Leadership received by Life Way Tech India Pvt. Ltd. Amit Kant Pandit, PhD, is an associate professor in the School of Electronics & Communication Engineering Shri Mata Vaishno Devi University, India. He has authored/co-authored more than 60 publications including peer-reviewed journals and conferences. He has two Indian and one Australian patent to his credit in artificial intelligence and image processing. His main research interests are image processing, video compression, image segmentation, fuzzy entropy, and nature-inspired computing methods with applications in optimization. Nitish Pathak, PhD, is an associate professor in the Department of Information Technology, Bhagwan Parshuram Institute of Technology, New Delhi, India. He has 17 years of engineering education experience and has published more than 80 journal articles, in peer-reviewed journals as well as book chapters, patents, and conference papers. His research areas include intelligent computing techniques, empirical software engineering, and artificial intelligence.

    Innehållsförteckning

    • Preface xv1 Advancement in Diagnostic and Therapeutic Techniques for Ischemic Stroke 1Mukul Jain, Divya Patil, Shubham Gupta and Shubham Mahajan1.1 Introduction 21.2 Diagnostic Tools of Ischemic Stroke 41.3 Artificial Intelligence–Based Diagnostic Tools 71.4 Blood-Based Protein Biomarker for Stroke 81.5 Markers for Endothelial Damage 81.6 Markers of Brain Injury 91.7 Therapeutic Advances in Ischemic Stroke 91.8 Nanoparticles 111.9 Conclusion 132 Object Detection and Tracking Face Detection and Recognition 25Varsha K. Patil, Pawan Nawade, Rudra Nagarkar and Paresh Kadale2.1 Introduction 252.2 Motivation 302.3 The Basics of Computer Vision 312.4 Face Detection 342.5 Facial Expression 382.6 Object Detection 412.7 Face Detection and Identification in Practical Situations 442.8 Future Direction in Object Detection and Tracking 472.9 Conclusion 523 Printing Organs with 3D Technology 55Shaik Aminabee3.1 Introduction 553.2 Bioprinting in Three Dimensions (3D) 563.3 3D Printing Types 573.4 Applications for 3D Printing in Cells 603.5 New Developments 653.6 Progress in India 663.7 Limitation 673.8 A Future Point of View 673.9 Conclusion 684 Comparative Evaluation of Machine Learning Algorithms for Bank Fraud Detection 71Kiran Jot Singh, Divneet Singh Kapoor, Kunal Ranjan Singh, Chirag Kalucha, Gatik Alagh, Khushal Thakur and Anshul Sharma4.1 Introduction 714.2 Proposed Framework 734.3 Results 744.4 Concluding Remarks and Future Scope 775 An Overview of Computational-Based Strategies for Drug Repositioning 81Shalu Verma, Nidhi Nainwal, Alka Singh, Gauree Kukreti and Kiran Dobhal5.1 Introduction 815.2 Drug Repositioning 825.3 Challenges and Opportunities for Drug Repurposing 935.4 Conclusion 946 Improving Performance With Feature Selection, Extraction, and Learning 99Varsha K. Patil, Vrinda Shinde, Ritika Singh and Vipul Singh6.1 Introduction 996.2 Feature Selection 1006.3 Feature Extraction 1106.4 Feature Learning 1156.5 Future Research and Development 1236.6 Future Scope 1246.7 Conclusion 1257 Fusion of Phase and Local Features for CBIR 129Pooja Sharma7.1 Introduction 1297.2 Overview of the Proposed System 1327.3 Proposed Hybrid-Shape Descriptors 1327.4 Similarity Measurement 1377.5 Experimental Study and Performance Evaluation 1397.6 Conclusions 1478 Trading Bot for Cryptocurrency Market Based on Smart Price Action Strategies 151Divneet Singh Kapoor, Kiran Jot Singh, Anshoom Jain, Rhythm Chauhan, Khushal Thakur and Anshul Sharma8.1 Introduction 1518.2 Background 1548.3 Proposed Framework 1568.4 Results 1588.5 Conclusion and Future Scope 1619 Comparative Evaluation and Prediction of Exoplanets Using Machine Learning Methods 163Divneet Singh Kapoor, Kiran Jot Singh, Ashirvad Singh, Benarji Mulakala, Karan Singh, Prashant, Ramanjeet Singh and Shubham Mahajan9.1 Introduction 1649.2 Background 1679.3 Proposed Framework 1699.4 Results 1719.5 Conclusion and Future Scope 18210 The Risk of Using Failure Rate With the Help of MTTF and MTBF to Calculate Reliability 185Harpreet Kaur and Shiv Kumar Sharma10.1 Introduction 18510.2 Failure 18610.3 Conclusion 19111 A Detailed Description on Various Techniques of Edge Detection Algorithms 193Pritha A. and G. Fathima11.1 Introduction 19311.2 Edge Detection Techniques 19411.3 Experimental Results 20311.4 Comparative Results 20311.5 Conclusion 20311.6 Future Work 20412 Advancement of ML in Smart House 207Gokula Udhayan V., K. Mahaeshwari and N. Vinoth Kumar12.1 Objective 20712.2 Introduction 20712.3 Smart House System With IoT 20812.4 Future Scope 22312.5 Conclusion 22313 Multi-Robot Navigation: A Biologically Inspired Framework 225Imran Mir and Faiza Gul13.1 Introduction 22513.2 Optimization Algorithms 22613.3 Algorithms and Self-Organization 23613.4 Future Research Directions 23813.5 Conclusion 23914 Bidirectional LSTM for Heart Arrhythmia Detection 243Nikhil M. Agrawal, H. D. Bhanu Cheitanya, Abhishek Kumar Rai and Shubham Mahajan14.1 Introduction 24314.2 About the Dataset 24514.3 Flow of the Model 24614.4 Results 24814.5 Conclusion 24815 Study on Content-Based Image Retrieval 253Thanga Subha Devi M., R. Suji Pramila and Tibbie Pon Symon15.1 Introduction 25415.2 Related Works 25615.3 Extraction of Features 26115.4 User Interactions for CBIR System 26615.5 Conclusions 26916 Machine Learning and Angiogenesis in Cancer 273Dharambir Kashyap, Riya Sharma, Neelam Goel and Vivek Kumar Garg16.1 Introduction 27316.2 History of Angiogenesis Discovery 27416.3 Overview of Angiogenesis 27416.4 Angiogenesis in Carcinogenesis 27516.5 Molecular Mechanisms of Angiogenesis Formation 27616.6 Angiogenesis as a Target in Cancer Therapy 27616.7 Machine Learning Approaches in Angiogenesis 27716.8 Conclusion 27817 Handwritten Image Enhancement Based on Neutroscopic-Fuzzy and K-Mean Clustering 283Jaspreet Kaur, Divya Gupta, Simarjeet Kaur and Amrinder Singh17.1 Introduction 28417.2 Application of Image Processing 28617.3 Enhancement of Handwritten Document 28717.4 Clustering Techniques 28817.5 Performance Parameters 29017.6 Results and Discussion 29317.7 Conclusion 29518 A Texture Classification System Based on an Adaptive Histogram Equalized Shearlet Transform 299K. Gopalakrishnan, V. Karthikeyan and P.T. Vanathi18.1 Introduction 29918.2 Literature Survey 30318.3 Materials and Methods 30518.4 Proposed Methodology 30918.5 Result and Discussion 31118.6 Conclusion 32019 A Thyroid Nodule Detection Using L1-Norm Inception Deep Neural Network 323Saranya G.19.1 Introduction 32319.2 Related Work 32419.3 Methodology 32519.4 Results and Discussion 32919.5 Conclusion 336References 337Index 339