deep learning object detection (199 Ergebnisse)

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Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 96 | Sprache: Englisch | Produktart: Bücher.

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Taschenbuch. Zustand: Neu. Neuware - Accurately detecting crack localization is not an easy task. This book addresses important issues in detecting crack-like objects and provides a practical smart pavement surface inspection system using deep learning.

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Taschenbuch. Zustand: Neu. Neuware -The journey of writing this piece begins during our graduation period. After a long search we selected 'Application of Deep Learning In Object Detection'. We read all most 40 papers and came to a conclusion that we should go for combining our work for those who really are interested in this area. We comprehended all most all piece of our work and have included in simple and easy language so that reader can easy understand and get it.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch.

Taschenbuch. Zustand: Neu. Neuware -The era of digitization has paved the way for the emergence of multimedia technologies. The multimedia applications use a large video database. Applications such as video surveillance, traffic monitoring and live streaming of events need continuous monitoring of the video. Thus the video surveillance system for tracking multiple target objects from videos is one of the important research works. Video surveillance has many challenges such as inter-object occlusion, object confusion, different posing, environment with heavy clutter, the small size of objects, similar appearance among objects, and interaction among the multiple objects. The hybrid tracking model utilizes the spatial tracking model, based on the tangential weighed function and the visual tracking model based on the second derivative model.Books on Demand GmbH, Überseering 33, 22297 Hamburg 188 pp. Englisch.

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Taschenbuch. Zustand: Neu. Neuware -All countries agree on the need to find solutions to the problems in agriculture field and to determine the future of agriculture. The importance of artificial intelligence in agriculture is emphasized and encouraged due to issues such as climate changes, population growth, use of resources, and food security. Artificial intelligence applications are used to support advanced agricultural production, while providing opportunities for more efficient production. Artificial intelligence, which replaces human power in production, paves the way for the development of new technologies that can cultivate, sow, irrigate, harvest, analyze soil and plant status. It is thought that artificial intelligence technologies, which affect every institution in the sector from small producers to large enterprises, will gain a large place in the agricultural sector in the medium term. It is possible to divide artificial intelligence applications into groups in agriculture. These are in the form of agricultural robots, soil and crop monitoring, analytical forecasting. Applications that bring the future to today in production activities have shown that data collection is of primary importance.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch.

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Taschenbuch. Zustand: Neu. Neuware -Many real-life machine learning applications are increasingly guiding into focus on object detection and recognition. The traditional computer vision approaches do not achieve the needed accuracies. Deep learning-based approaches have achieved high accuracy levels raising the interest in such approaches in recent years. License plate detection and recognition have been extensively studied over the decades. However, more accurate and national/language-independent approaches are still in the focus of today¿s demand. In this book, we discuss an approach to detect and recognize multinational and multilingual license plates. The approach has four modules and each module is implemented using convolutional neural network architecture. The YOLOv2 detector with ResNet core network is utilized for license plate detection module. Faster R-CNN detector with a custom core network architecture is used for character segmentation module. Low complexity convolutional neural network architectures for license plate classification and character recognition modules are analyzed and studied. Each module is trained and tested separately and used to build end-to-end license plate recognition system.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2024-09 Pages: 208 Publisher: Publishing House of Electronic Industry This book introduces the application of deep learning in the field of image target detection and recognition. mainly including image defogging algorithm based on U. image enhancement algorithm based on feature fusion GAN. image super-resolution reconstruction algorithm based on ERGAN. image segmentation algorithm based on nested U. underwater dam crack image segmentation algorithm based.

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paperback. Zustand: New. Language:Chinese.Paperback.Pub Date:2022-02-01 Pages:233 Publisher:Wuhan University Press The book is divided into 6 chapters. Chapter 1 Deep Learning Theoretical Basis. expounds artificial intelligence. machine learning. deep learning theory. technology and methods and the relationship between the three. Chapter 2. Artificial Neural Network Model. summarizes the architecture. types. working principles and optimal training methods of neural networks. Chapter 3 Convolutional Neural Networks. a.

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paperback. Zustand: New. Paperback. Pub Date: 2023-09 Pages: 572 Publisher: China Machine Press Based on real data sets. this book comprehensively and systematically explains practical techniques. methods and practices of modern computer vision. covering more than 50 computer vision problems. The book is divided into four parts: the first part (Chapters 1-3) introduces the basics of neural networks and PyTorch. and how to use PyTorch to build and train neural networks. including input data scaling. batch normalizatio.

Taschenbuch. Zustand: Neu. Neuware -This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.

Buch. Zustand: Neu. Neuware -This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing. It provides a systematic and methodical overview of the latest developments in deep learning theory and its applications to computer vision, illustrating them using key topics, including object detection, face analysis, 3D object recognition, and image retrieval.The book offers a rich blend of theory and practice. It is suitable for students, researchers and practitioners interested in deep learning, computer vision and beyond and can also be used as a reference book. The comprehensive comparison of various deep-learning applications helps readers with a basic understanding of machine learning and calculus grasp the theories and inspires applications in other computer vision tasks.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2020-07-01 Pages: 220 Publisher: Machinery Industry Press This book introduces the core of convolutional neural networks-the intricate details and the subtleties of the algorithm.?It mainly includes advanced topics of convolutional neural networks and object detection using Keras and TensorFlow.?Contents: Foreword Acknowledgements Chapter 1 Introduction and Setting up the Development Environment 1 1.1 GitHub Repository and Supporting Website 2 1.2 Essenti.

paperback. Zustand: New. Paperback. Pub Date: 2022-11-01 Pages: 288 Language: Chinese Publisher: Electronic Industry Press The theories and methods in the relevant papers are presented to readers. and at the same time. in-depth analysis and explanations are made on the difficulties encountered by the author in the process of deep learning teaching. This book focuses on the introduction of convolutional neural networks. but the content of deep learning does not stop there. Therefore. the author divides deep learning i.