Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Advances In Detection And Classification Of Underwater Targets Using Synthetic Aperture Sonar Imagery PDF full book. Access full book title Advances In Detection And Classification Of Underwater Targets Using Synthetic Aperture Sonar Imagery.
| Author | : Tai Fei |
| Publisher | : |
| Total Pages | : 123 |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
| Author | : Vincent Myers |
| Publisher | : Cambridge Scholars Publishing |
| Total Pages | : 296 |
| Release | : 2014-06-12 |
| Genre | : Technology & Engineering |
| ISBN | : 1443861529 |
This book consists of the proceedings of the International Conference on Detection and Classification of Underwater Targets which took place in Brest, France, in October 2012. This collection of academic papers represents the current state of the art of research and development in the areas of sensor technology, processing, modeling and automation for the purpose of detecting and classifying objects in the underwater environment, written by leading researchers in government, industry and academia. These articles should be of interest not only to those working on underwater target detection, but also to researchers in the related fields of remote sensing, robotic perception and medical imaging.
| Author | : Sergio Silva |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 254 |
| Release | : 2009-02-01 |
| Genre | : Technology & Engineering |
| ISBN | : 3902613483 |
The demand to explore the largest and also one of the richest parts of our planet, the advances in signal processing promoted by an exponential growth in computation power and a thorough study of sound propagation in the underwater realm, have lead to remarkable advances in sonar technology in the last years.The work on hand is a sum of knowledge of several authors who contributed in various aspects of sonar technology. This book intends to give a broad overview of the advances in sonar technology of the last years that resulted from the research effort of the authors in both sonar systems and their applications. It is intended for scientist and engineers from a variety of backgrounds and even those that never had contact with sonar technology before will find an easy introduction with the topics and principles exposed here.
| Author | : Raiid Ahmed |
| Publisher | : |
| Total Pages | : |
| Release | : 2021 |
| Genre | : |
| ISBN | : |
In the past 10 years, advancements in graphical and cloud computing have made it possible to conduct a wide variety of experiments applying machine learning tools to real-world physical problems. In this thesis, we explore the effectiveness of applying these tools to an image classification problem dealing with SAS (Synthetic Aperture Sonar) imagery. Lack of reference SAS imagery means that training an image recognition algorithm would require creating a training dataset from the ground up. SAS imagery is computationally expensive to create which makes training an image classification algorithm non-trivial. Therefore, in this experiment we will leverage the use of artificially generated images from MATLAB to train our image classification algorithm. This algorithm will be validated on 3D-printed versions of the artificially generated images. The MNIST dataset will be used as a basis for both the set of artificially generated images and the set of 3D-printed models. The Fast.ai library will be used as the source for our image classification models. First returns of data show the classifier is able to categorize MATLAB generated training set at an accuracy rate of 99.5%. However, results are inconclusive for SAS data. Possible continuations of this study would explore the possibility of using numerical data rather than images, or categorizing scans based on material properties (ex: density).
| Author | : Andrzej Stateczny |
| Publisher | : MDPI |
| Total Pages | : 468 |
| Release | : 2021-01-22 |
| Genre | : Science |
| ISBN | : 3039439715 |
The Special Issue “Radar and Sonar Imaging Processing” is a collection of 21 articles exploring many topics related to remote sensing with radar and sonar sensors. In this editorial, we present short introductions of the published articles. The series of articles in this SI deal with a broad profile of aspects of the use of radar and sonar images in line with the latest scientific trends while making use of the latest developments in science, including artificial intelligence. It can be said that both radar and sonar imaging and processing still remain a “hot topic” and much research in this area is being conducted worldwide. New techniques and methods for extracting information from radar and sonar sensors and data have been proposed and verified. Some of these will stimulate further research while others have reached maturity and can be considered for industrial implementation and development.
| Author | : Xuebo Zhang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 281 |
| Release | : 2023-07-04 |
| Genre | : Science |
| ISBN | : 2832528740 |
| Author | : Cyril Goutte |
| Publisher | : Springer Nature |
| Total Pages | : 588 |
| Release | : 2020-05-05 |
| Genre | : Computers |
| ISBN | : 3030473589 |
This book constitutes the refereed proceedings of the 33rd Canadian Conference on Artificial Intelligence, Canadian AI 2020, which was planned to take place in Ottawa, ON, Canada. Due to the COVID-19 pandemic, however, it was held virtually during May 13–15, 2020. The 31 regular papers and 24 short papers presented together with 4 Graduate Student Symposium papers were carefully reviewed and selected from a total of 175 submissions. The selected papers cover a wide range of topics, including machine learning, pattern recognition, natural language processing, knowledge representation, cognitive aspects of AI, ethics of AI, and other important aspects of AI research.
| Author | : |
| Publisher | : |
| Total Pages | : |
| Release | : 2008 |
| Genre | : Image analysis |
| ISBN | : |
Autonomous Underwater Vehicles (AUVs) are increasingly being used by military forces to acquire high-resolution sonar imagery, in order to detect mines and other objects of interest on the seabed. Automatic detection and classification techniques are being developed for several reasons: to provide reliable and consistent detection of objects on the seabed; to free human analysts from time-consuming and tedious detection tasks; and to enable autonomous in-field decision-making based on observations of mines and other objects. This document reviews progress in the development of automated detection and classification techniques for side-looking sonars mounted on AUVs. Whilst the techniques have not yet reached maturity, considerable progress has been made in both unsupervised and supervised (trained) algorithms for feature detection and classification. In some cases, the performance and reliability of automated detection systems exceed those of human operators.
| Author | : |
| Publisher | : |
| Total Pages | : 4 |
| Release | : 2010 |
| Genre | : |
| ISBN | : |
When resurveying a seafloor area of interest during change detection operations, an automated method to match found bottom objects with objects detected in a previous survey allows the surveyor to quickly sort new objects from old. The change detection system developed at the Naval Research Laboratory contains modules for automatic object detection, feature matching using shadow outlining, scene matching using control-point matching, and visualization capabilities. This system was developed for sidescan sonar surveys using instrumentation such as the high-frequency Marine Sonic Technology sidescan sonar. In this paper, the authors describe modifications to the sidescan-based system required to perform change detection using Synthetic Aperture Sonar (SAS) bottom imagery.
| Author | : David Ribas |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 152 |
| Release | : 2010-07-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3642140394 |
Robotics is undergoing a major transformation in scope and dimension. From a largely dominant industrial focus, robotics is rapidly expanding into human en- ronments and vigorously engaged in its new challenges. Interacting with, assisting, serving, and exploring with humans, the emerging robots will increasingly touch people and their lives. Beyond its impact on physical robots, the body of knowledge robotics has p- duced is revealing a much wider range of applications reaching across diverse research areas and scienti?c disciplines, such as: biomechanics, haptics, neu- sciences, virtual simulation, animation, surgery, and sensor networks among others. In return, the challenges of the new emerging areas are proving an abundant source of stimulation and insights for the ?eld of robotics. It is indeed at the intersection of disciplines that the most striking advances happen. The SpringerTracts in AdvancedRobotics(STAR) is devoted to bringing to the research community the latest advances in the robotics ?eld on the basis of their signi?cance and quality. Through a wide and timely dissemination of critical - search developments in robotics, our objective with this series is to promote more exchanges and collaborations among the researchers in the community and c- tribute to further advancements in this rapidly growing ?eld.
