deep learning image processing (43 Ergebnisse)

Paperback. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Zustand: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: Very Good. 1762442714. 11/6/2025 3:25:14 PM.

Paperback. Zustand: Brand New. 20 pages. 8.50x0.04x11.00 inches. In Stock.

Paperback. Zustand: Very Good. Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality. Key Features Develop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and Python Apply machine learning and deep learning techniques with TensorFlow and Keras Discover the modern design patterns you should avoid when developing efficient computer vision applications Book DescriptionOpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language. In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras. By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep learning web applications Who this book is forThis book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Zustand: Very Good. A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more Key Features Discover how to build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection and video analysis Learn how to run your models on mobile devices and web pages and improve their performance Book DescriptionComputer vision solutions are becoming increasingly common, making their way into fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface. You'll then move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build generative adversarial networks (GANs) and variational autoencoders (VAEs) to create and edit images, and long short-term memory networks (LSTMs) to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learn Create your own neural networks from scratch Classify images with modern architectures including Inception and ResNet Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net Tackle problems faced when developing self-driving cars and facial emotion recognition systems Boost your application's performance with transfer learning, GANs, and domain adaptation Use recurrent neural networks (RNNs) for video analysis Optimize and deploy your networks on mobile devices and in the browser Who this book is forIf you're new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you're an expert curious about the new TensorFlow 2 features, you'll find this book useful. While some theoretical concepts require knowledge of algebra and calculus, the book covers concrete examples focused on practical applications such as visual recognition for self-driving cars and smartphone apps. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Hardcover. Zustand: Fine.

Paperback. Zustand: Brand New. 71 pages. 6.00x0.16x9.00 inches. In Stock.

Paperback. Zustand: Brand New. 343 pages. 9.00x6.25x0.75 inches. In Stock.

204 p. Seiten Book in very good condition. Sprache: Englisch Gewicht in Gramm: 440.

Zustand: New.

paperback. Zustand: Sehr gut. 372 Seiten; 9781788830645.2 Gewicht in Gramm: 1.

Taschenbuch. Zustand: Neu. Neuware - The future of the world depends upon latest technologies and innovative ideas. The innova- tive concepts help to upgrade our knowledge. Technology is changing how people purchase grocery products, clothes, and other products. With retailers hopping on the cashier-less bandwagon in an effort to attract time-crunched shoppers, emerging technologies are help- ing them make this possible. The retail sector is changing dynamically with all the videos captured in unconstrained real-world scenarios is an interesting problem with many po- tential applications. This report presents an efficient approach to digital image processing techniques, face detection algorithms, and object detection algorithms. In this report we talk about the future of Retail Shops where in people can just take the item they want and leave the store without waiting in the checkout line. The AI that controls the environment follows each customer, noting each item taken and any that may be put back, so no errors are made and there are no charges for products not brought home.

hardcover. Zustand: Very Good.

hardcover. Zustand: Fine.

Zustand: as new. edition 2019. vendeur professionnel; envoi soigne en 24/48h.

Taschenbuch. Zustand: Neu. Introduction to Deep Learning Business Applications for Developers | From Conversational Bots in Customer Service to Medical Image Processing | Bernardete Ribeiro (u. a.) | Taschenbuch | xxi | Englisch | 2018 | Apress | EAN 9781484234525 | Verantwortliche Person für die EU: APress in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Neuware -This book summarizes the financial activities are carrying out in every second by many persons in which one most important asset of our country is Banknotes. Fake notes are introduced in the market to create discrepancies in the financial market, even they resemble to the original note. Now days, supervised machine learning (SML) approaches for classification problem is widely used. For medical disease its shows even promising result. Few authors have only applied SML algorithms on bank currency authentication. In this study, there are several things that can be from the results of machine learning using Error Level analysis and Convolutional Neural Network.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch.

Taschenbuch. Zustand: Neu. Biologically Inspired Hexagonal Deep Learning for Hexagonal Image Processing | Tobias Schlosser | Taschenbuch | Englisch | Universitätsverlag Chemnitz | EAN 9783961002139 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Deep Learning based Image Processing | Cashier-less Self-Checkout Methodology | Amol Dumbare | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203840315 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Deep Learning and Image Processing-Based Currency Detection | M. Aravaind Kumar (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206164517 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Neuware -This thesis optimizes AI models for identifying tool wear on microscopic images of cutting tools. It creates a tool wear model from empirical trials to generate a dataset and conducts screening analysis to find key factors affecting AI performance. A decision model for dataset-specific hyperparameters is developed. The model is validated with practical use cases. The work enhances tool wear management in manufacturing, enabling timely maintenance, reducing scrap, and lowering costs.Books on Demand GmbH, Überseering 33, 22297 Hamburg 182 pp. Englisch.

Zustand: good. Befriedigend/Good: Durchschnittlich erhaltenes Buch bzw. Schutzumschlag mit Gebrauchsspuren, aber vollständigen Seiten. / Describes the average WORN book or dust jacket that has all the pages present.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

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Taschenbuch. Zustand: Neu. Automated Flank Wear Segmentation and Measurement with Deep Learning Image Processing | Carsten Holst | Taschenbuch | Englisch | 2025 | Apprimus Verlag | EAN 9783985552610 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Zustand: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Zustand: New.

Zustand: New.

Taschenbuch. Zustand: Neu. Neuware - Deep Learning for Multimedia Processing Applications is a comprehensive guide that explores the revolutionary impact of deep learning techniques in the field of multimedia processing. Written for a wide range of readers, from students to professionals, this book offers a concise and accessible overview of the application of deep learning in various multimedia domains, including image processing, video analysis, audio recognition, and natural language processing.