Mohammed Ghazal – författare
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3 produkter
3 produkter
2 310 kr
Skickas inom 10-15 vardagar
The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field.
747 kr
Skickas inom 10-15 vardagar
The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methodsCovers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformationDescribes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentationIs aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineeringThis is an essential reference for those looking to advance their understanding in this applied and emergent field.
Towards Sustainable Futures with Artificial Intelligence and Data Innovation
Inbunden, Engelska, 2026
3 232 kr
Kommande
This book presents a multidisciplinary exploration of artificial intelligence, digital transformation, and sustainability across education, energy, healthcare, urban systems, governance, and socio-economic development. Besides environmental communication, the book examines the role of generative AI in enhancing the quality of higher education, critically assesses the conceptual foundations of artificial intelligence and investigate its application in optimizing green hydrogen production and carbon footprint prediction. Several contributions focus on AI-driven solutions in healthcare, including real-time ECG monitoring, prostate cancer classification, health information systems, and digital platforms for early childhood parenting education. The book also addresses AI adoption in humanitarian logistics, construction management, cybersecurity, and organizational performance, highlighting the mediating and moderating factors that influence successful implementation. Urban and regional perspectives are explored through smart cities, eco-districts, digital twins for mobility, and sustainable urban development models, alongside discussions on smart governance, public leadership, and regional transformation in the Mediterranean context. Collectively, the book provides theoretical insights, empirical evidence, and practical frameworks that demonstrate how AI and digital technologies can drive sustainable, inclusive, and resilient development across multiple sectors.