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Author : Arjun Dixit
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book Tree Defects Image Classification Using Convolutional Neural Networks on a Small Dataset written by Arjun Dixit and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sherri Houmadi
Publisher :
ISBN 13 :
Total Pages : 150 pages
Book Rating : 4.:/5 (124 download)
Download or read book The Application of Convolutional Neural Networks to Classify Paint Defects written by Sherri Houmadi and published by . This book was released on 2020 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: Despite all of the technological advancements in computer vision, many companies still utilize human visual inspection to determine whether parts are good or bad. It is particularly challenging for humans to inspect parts in a fast-moving manufacturing environment. Such is the case at Aisin Manufacturing Illinois where this study will be testing the use of convolutional neural networks (CNNs) to classify paint defects on painted outside door handles and caps for automobiles. Widespread implementation of vision systems has resulted in advancements in machine learning. As the field of artificial intelligence (AI) evolves and improvement are made, diverse industries are adopting AI models for use in their applications. Medical imaging classification using neural networks has exploded in recent years. Convolutional neural networks have proven to scale very well for image classification models by extracting various features from the images. A goal of this study is to create a low-cost machine learning model that is able to quickly classify paint defects in order to identify rework parts that can be repaired and shipped. The central thesis of this doctoral work is to test a machine learning model that can classify the paint defects based on a very small dataset of images, where the images are taken with a smartphone camera in a manufacturing setting. The end goal is to train the model for an overall accuracy rate of at least 80%. By using transfer learning and balancing the class datasets, the model was trained to achieve an overall accuracy rate of 82%.
Author : Max Ferguson
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (125 download)
Download or read book Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning written by Max Ferguson and published by . This book was released on 2018 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quality control is a fundamental component of many manufacturing processes, especially those involving casting or welding. However, manual quality control procedures are often time-consuming and error-prone. In order to meet the growing demand for high-quality products, the use of intelligent visual inspection systems is becoming essential in production lines. Recently, Convolutional Neural Networks (CNNs) have shown outstanding performance in both image classification and localization tasks. In this article, a system is proposed for the identification of casting defects in X-ray images, based on the Mask Region-based CNN architecture. The proposed defect detection system simultaneously performs defect detection and segmentation on input images, making it suitable for a range of defect detection tasks. It is shown that training the network to simultaneously perform defect detection and defect instance segmentation results in a higher defect detection accuracy than training on defect detection alone. Transfer learning is leveraged to reduce the training data demands and increase the prediction accuracy of the trained model. More specifically, the model is first trained with two large, openly available image datasets before fine-tuning on a relatively small metal casting X-ray dataset. The accuracy of the trained model exceeds the state-of-the art performance of the Grupo de Inteligencia de Máquina database of X-ray images (GDXray) Castings dataset and is fast enough to be used in a production setting. The system also performs well on the GDXray Welds dataset. A number of in-depth studies are conducted to explore how transfer learning, multitask learning, and multi-class learning influence the performance of the trained system.
Author : Ritu Tiwari
Publisher : Springer Nature
ISBN 13 : 9819735262
Total Pages : 714 pages
Book Rating : 4.8/5 (197 download)
Download or read book Proceedings of International Conference on Computational Intelligence written by Ritu Tiwari and published by Springer Nature. This book was released on with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Mishra, Divya Upadhyay
Publisher : IGI Global
ISBN 13 : 1668449935
Total Pages : 298 pages
Book Rating : 4.6/5 (684 download)
Download or read book Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things written by Mishra, Divya Upadhyay and published by IGI Global. This book was released on 2022-09-23 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the development of innovative technologies, the study of industrial automation is obtaining extraordinary attention from academia, governments, researchers, and various industrial communities. The technical innovations in advanced technologies such as deep learning, blockchain, artificial intelligence of things (AIOT), and more have unlocked the potential for bringing intelligent automation and efficiency to the industries to control their various operations. These new technologies provide an efficient and secure way for industries to manage and develop products intelligently. Revolutionizing Industrial Automation Through the Convergence of Artificial Intelligence and the Internet of Things includes the recent advancements in exploring and developing AIOT-powered strategies and mechanisms for future industrial automation and transforming industrial functions and architectures to help improve various industrial operations. Covering topics such as convolutional neural networks, smart urban logistics, and industrial automation, this premier reference source is an excellent resource for computer scientists, IT managers, engineers, business leaders and executives, logistics managers, students and faculty of higher education, libraries, researchers, and academicians.
Author : Domingo Mery
Publisher : Springer Nature
ISBN 13 : 3030567699
Total Pages : 473 pages
Book Rating : 4.0/5 (35 download)
Download or read book Computer Vision for X-Ray Testing written by Domingo Mery and published by Springer Nature. This book was released on 2020-12-21 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: [FIRST EDITION] This accessible textbook presents an introduction to computer vision algorithms for industrially-relevant applications of X-ray testing. Features: introduces the mathematical background for monocular and multiple view geometry; describes the main techniques for image processing used in X-ray testing; presents a range of different representations for X-ray images, explaining how these enable new features to be extracted from the original image; examines a range of known X-ray image classifiers and classification strategies; discusses some basic concepts for the simulation of X-ray images and presents simple geometric and imaging models that can be used in the simulation; reviews a variety of applications for X-ray testing, from industrial inspection and baggage screening to the quality control of natural products; provides supporting material at an associated website, including a database of X-ray images and a Matlab toolbox for use with the book’s many examples.
Author : Saurabh Prasad
Publisher : Springer Nature
ISBN 13 : 3030386171
Total Pages : 464 pages
Book Rating : 4.0/5 (33 download)
Download or read book Hyperspectral Image Analysis written by Saurabh Prasad and published by Springer Nature. This book was released on 2020-04-27 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
Author : Valentina Emilia Balas
Publisher : Springer Nature
ISBN 13 : 9813349689
Total Pages : 795 pages
Book Rating : 4.8/5 (133 download)
Download or read book Proceedings of International Conference on Computational Intelligence, Data Science and Cloud Computing written by Valentina Emilia Balas and published by Springer Nature. This book was released on 2021 with total page 795 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.
Author : Niketa Penumajji
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (133 download)
Download or read book Deep Learning in Seed Image Classification Using Domain Randomization and Convolutional Neural Networks written by Niketa Penumajji and published by . This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this thesis is to study the application of deep learning in seed image classification using convolutional neural networks. The images are captured using an unmanned aerial vehicle as might be used in a plant breeding program. Plant breeding programs extensively monitor the evolution of seed kernels for seed certification, wherein lies the need to appropriately label the seed kernels by type and quality. However, the breeding environments are large where the monitoring of seed kernels can be challenging due to the relatively small size of seed kernels. For this experiment, we use an unpiloted aerial vehicle to capture images at low altitude while being able to access even the remotest areas in the environments. In a small breeding program, they might use fixed cameras instead. A key bottleneck in the labelling of seeds using UAV imagery is drone altitude, i.e., the classification accuracy decreases as drone altitude increases due to lower image detail. Convolutional neural networks are a great tool for multi-class image classification where there is a training dataset that closely represents the different scenarios that the network might encounter during evaluation. However, with the seeds being in a breeder environment coupled with the varying image resolution and clarity, it is challenging to generate a training dataset that covers all possible evaluation scenario. This work addresses the challenge of training data creation using Domain Randomization wherein synthetic image datasets are generated from a meager sample of seed images captured by the bottom camera of an autonomously driven Parrot AR Drone 2.0. Also, the work includes a seed classification framework as a proof-of-concept using the convolutional neural networks of Microsoft's ResNet-100, Oxford's VGG-16, and VGG-19. To enhance the classification accuracy of the framework, an ensemble model is developed resulting in an overall accuracy of 94.6%. The task of classification is performed on five distinct types of seeds, canola, rough rice, sorghum, soy, and wheat. The second use case is the drones are used for aerial surveying where the UAV imagery is used to estimate the area of a plot. The work demonstrates how the area can be calculated using the pixels of an image and the camera specifications of the drone.
Author : Dirk Burghardt
Publisher : Springer Nature
ISBN 13 : 3031353749
Total Pages : 298 pages
Book Rating : 4.0/5 (313 download)
Download or read book Volunteered Geographic Information written by Dirk Burghardt and published by Springer Nature. This book was released on 2023-12-08 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book includes methods for retrieval, semantic representation, and analysis of Volunteered Geographic Information (VGI), geovisualization and user interactions related to VGI, and discusses selected topics in active participation, social context, and privacy awareness. It presents the results of the DFG-funded priority program "VGI: Interpretation, Visualization, and Social Computing" (2016-2023). The book includes three parts representing the principal research pillars within the program. Part I "Representation and Analysis of VGI" discusses recent approaches to enhance the representation and analysis of VGI. It includes semantic representation of VGI data in knowledge graphs; machine-learning approaches to VGI mining, completion, and enrichment as well as to the improvement of data quality and fitness for purpose. Part II "Geovisualization and User Interactions related to VGI" book explores geovisualizations and user interactions supporting the analysis and presentation of VGI data. When designing these visualizations and user interactions, the specific properties of VGI data, the knowledge and abilities of different target users, and technical viability of solutions need to be considered. Part III "Active Participation, Social Context and Privacy Awareness" of the book addresses the human impact associated with VGI. It includes chapters on the use of wearable sensors worn by volunteers to record their exposure to environmental stressors on their daily journeys, on the collective behavior of people using location-based social media and movement data from football matches, and on the motivation of volunteers who provide important support in information gathering, filtering and analysis of social media in disaster situations. The book is of interest to researchers and advanced professionals in geoinformation, cartography, visual analytics, data science and machine learning.
Author : Shabir A. Parah
Publisher : Springer Nature
ISBN 13 : 3031348737
Total Pages : 363 pages
Book Rating : 4.0/5 (313 download)
Download or read book Intelligent Multimedia Signal Processing for Smart Ecosystems written by Shabir A. Parah and published by Springer Nature. This book was released on 2023-09-30 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: A smart ecosystem is envisioned to exchange and analyze data across systems, enabling a flexible, faster, and reliable smart ecosystem for high-quality results at reduced costs and little human intervention. This book introduces many innovative approaches and provides solutions to various problems of smart ecosystems designed by employing various techniques/models based on AI, ML, Deep Learning, and the Internet of Things (IoT). The main focus is on intelligent multimedia processing and automated decision-making for various services, real-time data analysis, data security, cost-effective solutions for multimedia applications, smart information processing systems, and smart city planning to name a few. In addition, this book presents some key insights and future directions in the various areas of technology. Throughout the book, many state-of-the-art solutions concerning various applications are proposed to solve the issues and ensure the quality of services (QoS). The authors discuss the limitations of the current techniques used to design a smart ecosystem and highlight some prospective areas of research in the future. The book comprehensively discusses multimedia processing of various forms of data comprising text, images, and audio for the implementation of various solutions. The book is aimed to open many areas of research and thus would present a comprehensive reference for the design of smart ecosystems in various applications.
Author : De-Shuang Huang
Publisher : Springer Nature
ISBN 13 : 3031138325
Total Pages : 928 pages
Book Rating : 4.0/5 (311 download)
Download or read book Intelligent Computing Methodologies written by De-Shuang Huang and published by Springer Nature. This book was released on 2022-08-15 with total page 928 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set of LNCS 13393 and LNCS 13394 constitutes - in conjunction with the volume LNAI 13395 - the refereed proceedings of the 18th International Conference on Intelligent Computing, ICIC 2022, held in Xi'an, China, in August 2022. The 209 full papers of the three proceedings volumes were carefully reviewed and selected from 449 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was “Advanced Intelligent Computing Technology and Applications”. Papers focused on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Author : Subarna Shakya
Publisher : Springer Nature
ISBN 13 : 9811676577
Total Pages : 911 pages
Book Rating : 4.8/5 (116 download)
Download or read book Proceedings of Second International Conference on Sustainable Expert Systems written by Subarna Shakya and published by Springer Nature. This book was released on 2022-02-26 with total page 911 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features high-quality research papers presented at the 2nd International Conference on Sustainable Expert Systems (ICSES 2021), held in Nepal during September 17–18, 2021. The book focusses on the research information related to artificial intelligence, sustainability, and expert systems applied in almost all the areas of industries, government sectors, and educational institutions worldwide. The main thrust of the book is to publish the conference papers that deal with the design, implementation, development, testing, and management of intelligent and sustainable expert systems and also to provide both theoretical and practical guidelines for the deployment of these systems.
Author : Pradeep Singh
Publisher : John Wiley & Sons
ISBN 13 : 1119821886
Total Pages : 480 pages
Book Rating : 4.1/5 (198 download)
Download or read book Fundamentals and Methods of Machine and Deep Learning written by Pradeep Singh and published by John Wiley & Sons. This book was released on 2022-02-01 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.
Author : Jucheng Yang
Publisher : Frontiers Media SA
ISBN 13 : 2832550096
Total Pages : 350 pages
Book Rating : 4.8/5 (325 download)
Download or read book Advanced AI Methods for Plant Disease and Pest Recognition written by Jucheng Yang and published by Frontiers Media SA. This book was released on 2024-06-06 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plant diseases and pests cause significant losses to farmers and threaten food security worldwide. Monitoring the growing conditions of crops and detecting plant diseases is critical for sustainable agriculture. Traditionally, crop inspection has been carried out by people with expert knowledge in the field. However, regarding any activity carried out by humans, this activity is prone to errors, leading to possible incorrect decisions. Innovation is, therefore, an essential fact of modern agriculture. In this context, deep learning has played a key role in solving complicated applications with increasing accuracy over time, and recent interest in this type of technology has prompted its potential application to address complex problems in agriculture, such as plant disease and pest recognition. Although substantial progress has been made in the area, several challenges still remain, especially those that limit systems to operate in real-world scenarios.
Author : Zhiqin Zhu
Publisher : Frontiers Media SA
ISBN 13 : 283253693X
Total Pages : 207 pages
Book Rating : 4.8/5 (325 download)
Download or read book Multi-Sensor Imaging and Fusion: Methods, Evaluations, and Applications written by Zhiqin Zhu and published by Frontiers Media SA. This book was released on 2023-10-25 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Le Lu
Publisher : Springer
ISBN 13 : 331942999X
Total Pages : 327 pages
Book Rating : 4.3/5 (194 download)
Download or read book Deep Learning and Convolutional Neural Networks for Medical Image Computing written by Le Lu and published by Springer. This book was released on 2017-07-12 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
