Zhu, Hu.
Infrared Small Target Detection Theory, Methods, and Algorithms. / [electronic resource] : by Hu Zhu, Yushan Pan, Lizhen Deng, Guoxia Xu. - 1st ed. 2024. - XIV, 168 p. 1 illus. online resource.
Chapter 1: Introduction -- Chapter 2: Preliminaries.-Chapter 3: Morphological Transformation for infrared small object detection -- Chapter 4: Low-rank tensor decomposition for infrared small object detection -- Chapter 5: Deep learning methods for infrared small object detection -- Chapter 6: Performance of different methods. Chapter 7: Summary and Outlook of research on infrared small target detection.
Uncover the secrets of cutting-edge research in "Infrared Small Target Detection," a crucial resource that delves into the dynamic world of infrared imaging and detection algorithms. This comprehensive book is an indispensable gem for the research community, offering a profound introduction to the theory, methods, and algorithms underlying infrared small object detection. As an invaluable guide, this book explores diverse models and categories of infrared small object detection algorithms, providing meticulous descriptions and comparisons of their strengths and limitations. Perfectly tailored for researchers, practitioners, and students with a passion for infrared imaging and detection, this book equips readers with the necessary knowledge to embark on groundbreaking investigations in this field.Readers can particularly be drawn to the book's methods, results, and topics, encompassing diverse categories of infrared small object detection algorithms and their corresponding advantages and disadvantages. The book also imparts foundational knowledge in mathematical morphology, tensor decomposition, and deep learning, enabling readers to grasp the underlying principles of these advanced algorithms. Experience the key benefits of "Infrared Small Target Detection" as readers gain a profound understanding of theory, methods, and algorithms tailored to infrared small object detection. The comprehensive descriptions and comparisons of various algorithm categories empower readers to select the perfect algorithms for their specific applications. Unlock the potential of this groundbreaking resource with a basic understanding of mathematics, statistics, and image processing. Some familiarity with infrared imaging and detection proves advantageous in fully immersing oneself in the wealth of knowledge presented within these pages.
9789819997992
10.1007/978-981-99-9799-2 doi
Image processing--Digital techniques.
Computer vision.
Artificial intelligence.
Computer science--Mathematics.
Computer science.
Software engineering.
Programming languages (Electronic computers).
Computer Imaging, Vision, Pattern Recognition and Graphics.
Artificial Intelligence.
Mathematics of Computing.
Theory of Computation.
Software Engineering.
Programming Language.
TA1501-1820 TA1634
006
Infrared Small Target Detection Theory, Methods, and Algorithms. / [electronic resource] : by Hu Zhu, Yushan Pan, Lizhen Deng, Guoxia Xu. - 1st ed. 2024. - XIV, 168 p. 1 illus. online resource.
Chapter 1: Introduction -- Chapter 2: Preliminaries.-Chapter 3: Morphological Transformation for infrared small object detection -- Chapter 4: Low-rank tensor decomposition for infrared small object detection -- Chapter 5: Deep learning methods for infrared small object detection -- Chapter 6: Performance of different methods. Chapter 7: Summary and Outlook of research on infrared small target detection.
Uncover the secrets of cutting-edge research in "Infrared Small Target Detection," a crucial resource that delves into the dynamic world of infrared imaging and detection algorithms. This comprehensive book is an indispensable gem for the research community, offering a profound introduction to the theory, methods, and algorithms underlying infrared small object detection. As an invaluable guide, this book explores diverse models and categories of infrared small object detection algorithms, providing meticulous descriptions and comparisons of their strengths and limitations. Perfectly tailored for researchers, practitioners, and students with a passion for infrared imaging and detection, this book equips readers with the necessary knowledge to embark on groundbreaking investigations in this field.Readers can particularly be drawn to the book's methods, results, and topics, encompassing diverse categories of infrared small object detection algorithms and their corresponding advantages and disadvantages. The book also imparts foundational knowledge in mathematical morphology, tensor decomposition, and deep learning, enabling readers to grasp the underlying principles of these advanced algorithms. Experience the key benefits of "Infrared Small Target Detection" as readers gain a profound understanding of theory, methods, and algorithms tailored to infrared small object detection. The comprehensive descriptions and comparisons of various algorithm categories empower readers to select the perfect algorithms for their specific applications. Unlock the potential of this groundbreaking resource with a basic understanding of mathematics, statistics, and image processing. Some familiarity with infrared imaging and detection proves advantageous in fully immersing oneself in the wealth of knowledge presented within these pages.
9789819997992
10.1007/978-981-99-9799-2 doi
Image processing--Digital techniques.
Computer vision.
Artificial intelligence.
Computer science--Mathematics.
Computer science.
Software engineering.
Programming languages (Electronic computers).
Computer Imaging, Vision, Pattern Recognition and Graphics.
Artificial Intelligence.
Mathematics of Computing.
Theory of Computation.
Software Engineering.
Programming Language.
TA1501-1820 TA1634
006