Presents in-depth knowledge on the latest research in image processing and computer vision techniques, explaining the machine learning algorithms and models involved. The authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task.
Presents in-depth knowledge on the latest research in image processing and computer vision techniques, explaining the machine learning algorithms and models involved. The authors differentiate between the various algorithms available and how to choose which to use for the most precise results for a specific task.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Karm Veer Arya, PhD, is associated with the Department of Information and Communication at the ABV-Indian Institute of Information Technology and Management, Gwalior, India, where he is also Coordinator of the Multimedia and Information Security Research Group. He has more than 29 years of teaching and research experience. Prof. Arya has published more than 150 research papers in various internationally reputed journals and conferences. He has supervised 11 PhD scholars and nearly 100 postgraduate students. Prof. Arya is a recipient of several awards for his work. Ciro Rodriguez Rodriguez, PhD, is associated with the Department of Software Engineering at National University Mayor de San Marcos and with the Department of Informatic Engineering at National University Federico Villarreal, both in Lima, Peru. He has done advanced studies at the International Centre for Theoretical Physics in Italy, at the U.S. Particle Accelerator School, and at the Information Technology Development Policy Studies at Korea Telecom in South Korea. He has published over 80 research articles in reputed journals and has filed two patents in engineering fields. Saurabh Singh, PhD, is working as Professor at the School of Computing Science and Engineering, Galgotias University, Greater Noida, India. Dr. Singh has more than 21 years of experience in teaching and research. He has published over 40 research articles in various internationally reputed journals and conferences, written book chapters, and filed nine patents in various fields of engineering. Abhishek Singhal, PhD, is working as an Associate Professor in the Department of Computer Science and Engineering at Amity University, Noida, India. He has published over 50 Scopusindexed research articles in various internationally reputed journals and conferences.
Inhaltsangabe
PART I: HEALTHCARE SYSTEMS 1. Machine Learning Model-Based Detection of Sperm Head Abnormalities from Stained Microscopic Images 2. Smart Healthcare System for Reliable Diagnosis of Polycystic Ovary Syndrome 3. Classification of Breast Histopathological Images Using Semi-Supervised Generative Adversarial Networks 4. A Systematic Review for Classification and Segmentation of Diabetic Retinopathy Lesion from Fundus 5. Critical Analysis of Various Supervised Machine Learning Algorithms for Detecting Diabetic Retinopathy in Images PART II: IMAGE AND VIDEO PROCESSING 6. Artificial Bee Colony Optimization Technique-Based Video Copyright Protection in DWT-PCA Domain 7. Gray Tone Spatial Dependence Matrix: Texture Feature for Image Classification 8. Image Colorization and Restoration Using Deep Learning 9. Determining Image Scale in Real-World Units Using Natural Objects Present in Image 10. Image Segmentation Using Meta-Heuristics PART III: ADVANCED MACHINE LEARNING 11. A Computer Vision Use Case: Detecting the Changes in the Amazon Rainforest Over Time 12. Using CNN and Image Processing Approaches in the Preservation of Sea Turtles 13. Deep Learning-Based Semantic Segmentation Techniques and Their Applications in Remote Sensing 14. Deep Convolutional Neural Network-Based Single Image Superresolution 15. A Review of Machine Learning Techniques for Vision-Established Human Action Recognition
PART I: HEALTHCARE SYSTEMS 1. Machine Learning Model-Based Detection of Sperm Head Abnormalities from Stained Microscopic Images 2. Smart Healthcare System for Reliable Diagnosis of Polycystic Ovary Syndrome 3. Classification of Breast Histopathological Images Using Semi-Supervised Generative Adversarial Networks 4. A Systematic Review for Classification and Segmentation of Diabetic Retinopathy Lesion from Fundus 5. Critical Analysis of Various Supervised Machine Learning Algorithms for Detecting Diabetic Retinopathy in Images PART II: IMAGE AND VIDEO PROCESSING 6. Artificial Bee Colony Optimization Technique-Based Video Copyright Protection in DWT-PCA Domain 7. Gray Tone Spatial Dependence Matrix: Texture Feature for Image Classification 8. Image Colorization and Restoration Using Deep Learning 9. Determining Image Scale in Real-World Units Using Natural Objects Present in Image 10. Image Segmentation Using Meta-Heuristics PART III: ADVANCED MACHINE LEARNING 11. A Computer Vision Use Case: Detecting the Changes in the Amazon Rainforest Over Time 12. Using CNN and Image Processing Approaches in the Preservation of Sea Turtles 13. Deep Learning-Based Semantic Segmentation Techniques and Their Applications in Remote Sensing 14. Deep Convolutional Neural Network-Based Single Image Superresolution 15. A Review of Machine Learning Techniques for Vision-Established Human Action Recognition
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