Download or read book Deep Learning based Vehicle Detection in Aerial Imagery written by Sommer, Lars Wilko and published by KIT Scientific Publishing. This book was released on 2022-02-09 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes a novel deep learning based detection method, focusing on vehicle detection in aerial imagery recorded in top view. The base detection framework is extended by two novel components to improve the detection accuracy by enhancing the contextual and semantical content of the employed feature representation. To reduce the inference time, a lightweight CNN architecture is proposed as base architecture and a novel module that restricts the search area is introduced.
Download or read book Mulitple Vehicle Detection in Image and Video Using a Deep Learning Model with Aerial Images written by Samer Hmadi and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning Based Vehicle Detection in Aerial Imagery written by Lars Sommer and published by . This book was released on 2018 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Moving Object Detection and Segmentation for Remote Aerial Video Surveillance written by Teutsch, Michael and published by KIT Scientific Publishing. This book was released on 2015-03-11 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned Aerial Vehicles (UAVs) equipped with video cameras are a flexible support to ensure civil and military safety and security. In this thesis, a video processing chain is presented for moving object detection in aerial video surveillance. A Track-Before-Detect (TBD) algorithm is applied to detect motion that is independent of the camera motion. Novel robust and fast object detection and segmentation approaches improve the baseline TBD and outperform current state-of-the-art methods.
Download or read book Vehicle Detection Using Morphological Shared weight Neural Network in the Multiple Instance Learning Framework written by Anes Ouadou and published by . This book was released on 2017 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this thesis, we design and implement an algorithm for object detection in aerial images based on the morphological shared-weight neural network (MSNN). The multiple instance learning (MIL) framework is used to avoid the labeling problem required in a supervised learning framework. Using the MIL, each image was given a single label. We rely on the MSNN’s ability to detect objects, and on the methodology used to generate bags to find our target. Two multiple-instance MSNN structures are developed. The performance of this framework is compared with the performance of a convolutional neural network (CNN) in the same condition.
Download or read book Remote Sensing for Target Object Detection and Identification written by Gemine Vivone and published by MDPI. This book was released on 2020-03-06 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Target object detection and identification are among the primary uses for a remote sensing system. This is crucial in several fields, including environmental and urban monitoring, hazard and disaster management, and defense and military. In recent years, these analyses have used the tremendous amount of data acquired by sensors mounted on satellite, airborne, and unmanned aerial vehicle (UAV) platforms. This book promotes papers exploiting different remote sensing data for target object detection and identification, such as synthetic aperture radar (SAR) imaging and multispectral and hyperspectral imaging. Several cutting-edge contributions, which provide examples of how to select of a technology or another depending on the specific application, will be detailed.
Download or read book Modelling and Simulation for Autonomous Systems written by Jan Mazal and published by Springer Nature. This book was released on 2020-03-30 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 6th International Workshop on Modelling and Simulation for Autonomous Systems, MESAS 2019, held in Palermo, Italy, in October 2019. The 22 full papers and 13 short papers included in the volume were carefully reviewed and selected from 53 submissions. They are organized in the following topical sections: M&S of intelligent systems - AI, R&D and application; future challenges of advanced M&S technology; AxS in context of future warfare and security environment (concepts, applications, training, interoperability, etc.).
Download or read book Deep Learning for Computer Vision written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2019-04-04 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Download or read book Deep Learning Applications in Image Analysis written by Sanjiban Sekhar Roy and published by Springer Nature. This book was released on 2023-07-08 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art coverage of deep learning applications in image analysis. The book demonstrates various deep learning algorithms that can offer practical solutions for various image-related problems; also how these algorithms are used by scientists and scholars in industry and academia. This includes autoencoder and deep convolutional generative adversarial network in improving classification performance of Bangla handwritten characters, dealing with deep learning-based approaches using feature selection methods for automatic diagnosis of covid-19 disease from x-ray images, imbalance image data sets of classification, image captioning using deep transfer learning, developing a vehicle over speed detection system, creating an intelligent system for video-based proximity analysis, building a melanoma cancer detection system using deep learning, plant diseases classification using AlexNet, dealing with hyperspectral images using deep learning, chest x-ray image classification of pneumonia disease using efficient net and inceptionv3. The book also addresses the difficulty of implementing deep learning in terms of computation time and the complexity of reasoning and modelling different types of data where information is currently encoded. Each chapter has the application of various new or existing deep learning models such as Deep Neural Network (DNN) and Deep Convolutional Neural Networks (DCNN). The detailed utilization of deep learning packages that are available in MATLAB, Python and R programming environments have also been discussed, therefore, the readers will get to know about the practical implementation of deep learning as well. The content of this book is presented in a simple and lucid style for professionals, nonprofessionals, scientists, and students interested in the research area of deep learning applications in image analysis.
Download or read book Scanning Technologies for Autonomous Systems written by Julio C. Rodríguez-Quiñonez and published by Springer Nature. This book was released on with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Image and Video Technology written by Joel Janek Dabrowski and published by Springer Nature. This book was released on 2020-01-26 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of four international workshops held in the framework of the 9th Pacific-Rim Symposium on Image and Video Technology, PSIVT 2019, in Sydney, NSW, Australia, in November 2019: Vision-Tech: Workshop on Challenges, Technology, and Solutions in the Areas of Computer Vision; Workshop on Passive and Active Electro‐Optical Sensors for Aerial and Space Imaging; Workshop on Deep Learning and Image Processing Techniques for Medical Images; and Workshop on Deep Learning for Video and Image Analysis. The 16 revised full papers presented were carefully selected from 26 submissions. The papers cover the full range of state-of-the-art research in image and video technology with topics ranging from well-established areas to novel current trends.
Download or read book Artificial Intelligence and Computer Vision written by Huimin Lu and published by Springer. This book was released on 2016-11-01 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book presents essential findings in the research fields of artificial intelligence and computer vision, with a primary focus on new research ideas and results for mathematical problems involved in computer vision systems. The book provides an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis on the technical and observational results obtained in the past few years.
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.
Download or read book Remote Sensing Imagery written by Florence Tupin and published by John Wiley & Sons. This book was released on 2014-02-19 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to remote sensing images, from their acquisition to their use in various applications, this book covers the global lifecycle of images, including sensors and acquisition systems, applications such as movement monitoring or data assimilation, and image and data processing. It is organized in three main parts. The first part presents technological information about remote sensing (choice of satellite orbit and sensors) and elements of physics related to sensing (optics and microwave propagation). The second part presents image processing algorithms and their specificities for radar or optical, multi and hyper-spectral images. The final part is devoted to applications: change detection and analysis of time series, elevation measurement, displacement measurement and data assimilation. Offering a comprehensive survey of the domain of remote sensing imagery with a multi-disciplinary approach, this book is suitable for graduate students and engineers, with backgrounds either in computer science and applied math (signal and image processing) or geo-physics. About the Authors Florence Tupin is Professor at Telecom ParisTech, France. Her research interests include remote sensing imagery, image analysis and interpretation, three-dimensional reconstruction, and synthetic aperture radar, especially for urban remote sensing applications. Jordi Inglada works at the Centre National d’Études Spatiales (French Space Agency), Toulouse, France, in the field of remote sensing image processing at the CESBIO laboratory. He is in charge of the development of image processing algorithms for the operational exploitation of Earth observation images, mainly in the field of multi-temporal image analysis for land use and cover change. Jean-Marie Nicolas is Professor at Telecom ParisTech in the Signal and Imaging department. His research interests include the modeling and processing of synthetic aperture radar images.
Download or read book Intelligent Information and Database Systems written by Ngoc Thanh Nguyen and published by Springer. This book was released on 2019-04-02 with total page 745 pages. Available in PDF, EPUB and Kindle. Book excerpt: The two-volume set LNAI 11431 and 11432 constitutes the refereed proceedings of the 11th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2019, held in Yogyakarta, Indonesia, in April 2019. The total of 124 full papers accepted for publication in these proceedings were carefully reviewed and selected from 309 submissions. The papers of the first volume are organized in the following topical sections: knowledge engineering and semantic web; text processing and information retrieval; machine learning and data mining; decision support and control systems; computer vision techniques; and databases and intelligent information systems. The papers of the second volume are divided into these topical sections: collective intelligence for service innovation, technology management, E-learning, and fuzzy intelligent systems; data structures modelling for knowledge representation; advanced data mining techniques and applications; intelligent information systems; intelligent methods and artificial intelligence for biomedical decision support systems; intelligent and contextual systems; intelligent systems and algorithms in information sciences; intelligent supply chains and e-commerce; sensor networks and Internet of Things; analysis of image, video, movements and brain intelligence in life sciences; and computer vision and intelligent systems.
Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Download or read book Data Science written by Gyanendra K. Verma and published by Springer Nature. This book was released on 2021-08-19 with total page 444 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book targets an audience with a basic understanding of deep learning, its architectures, and its application in the multimedia domain. Background in machine learning is helpful in exploring various aspects of deep learning. Deep learning models have a major impact on multimedia research and raised the performance bar substantially in many of the standard evaluations. Moreover, new multi-modal challenges are tackled, which older systems would not have been able to handle. However, it is very difficult to comprehend, let alone guide, the process of learning in deep neural networks, there is an air of uncertainty about exactly what and how these networks learn. By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.
