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检索条件"任意字段=Conference on Mobile Multimedia/Image Processing for Military and Security Applications"

共 179 条记录，以下是121-130 订阅

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processing Global and Local Features in Convolutional Neural Network (CNN) and Primate Visual Systems

Processing Global and Local Features in Convolutional Neural...

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conference on mobile multimedia/image processing, security, and applications

作者： Zheng, Yufeng Huang, Jun Chen, Tianwen Ou, Yang Zhou, Wu Alcorn State Univ Lorman MS 39096 USA Univ Mississippi Med Ctr Jackson MS 39216 USA

ISBN: (数字)9781510618480

ISBN: (纸本)9781510618480

In the human visual system, visible objects are recognized by features, which can be classified into local features that are based on their simple components (i.e., line segment, angle, color, etc.) and global features that are based on the whole objects (i.e., connectivity, number of holes, etc.). Over the past half century, anatomical, physiological, behavioral and computational studies of the visual systems have led to a generally accepted model of vision, which starts at processing local features in the early stages of the visual pathways, followed by integrating them to global features in the later stages of the visual pathways. However, this popular local-to-global model has been challenged by a set of experiments showing that the visual systems in humans, non-human primates and honey bees are more sensitive to global features than local features. These "global-first" studies further motivated developing new paradigms and approaches to understand human vision and build new vision models. In this study, we started a new series of experiments that examine how two representative pre-trained Convolutional Neural Networks (CNN) (AlexNet and VGG-19) process local and global features. The CNNs were trained to classify geometric shapes into two categories based on local features (e.g., triangle, square and circle) or a global feature (e.g., having a hole). In contrast to the biological visual systems, the CNNs were more effective at classifying images based on local features than the global feature. We further showed that adding distractors greatly lowered the performance of the CNNs, again different from the biological visual systems. Ongoing studies will extend these analyses to other geometrical invariants and internal representations of the CNNs. The overarching goal is to use the powerful CNNs as a tool to gain insights into the biological visual systems, including that of humans and non-human primates.

关键词： Topological perception Visible object Local feature Global feature Convolutional Neural Network (CNN) AlexNet VGG-19 image classification

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Moving object detection from image sequence in context with multimedia processing

Moving object detection from image sequence in context with ...

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IET conference on Wireless, mobile and multimedia Networks

作者： Nagmode, M.S. Joshi, M.A. Pune University India Government College of Engg. Pune India

ISBN: (纸本)9780863418877

Research in motion analysis has evolved over the years as a challenging field. Moving object detection and tracking is of major interest in applications such as traffic monitoring, military, medicine and biological sciences etc. In this a new algorithm is proposed for the detection and tracking of moving objects. The image sequence is taken from the digital camera. After preprocessing, the first two frames from the image sequence are segmented by using 8 component connectivity. These segments/clusters are used as seeds for the next frame segmentation. From these segments centroid and area of each cluster is calculated. The Kalman estimation is used to estimate the centroid values for the next frame. The moving object is detected and tracked by using Kalman estimated centroid values. Estimated centroid values of the current frame and previous frames are compared and if there is enough change in the centroid position, it means it is the cluster which belongs to the moving object.

关键词： Object detection

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An Evaluation Framework for security Algorithms Performance Realization on FPGA

An Evaluation Framework for Security Algorithms Performance ...

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IEEE International conference on Current Trends in Advanced Computing (ICCTAC)

作者： Guruprasad, S. P. Chandrasekar, B. S. Jain Univ Dept ECE Bangalore Karnataka India Jain Univ CVLI Bangalore Karnataka India

ISBN: (纸本)9781538643228

security algorithms play a major role in most of the applications which include electronic gadgets, mobile banking, e-commerce, military, digital image processing, satellite & wireless communications, etc. The realization of the cryptography algorithm on FPGA is an open research problem to meet its benchmark to provide security essentials of confidentiality, integrity, and authentication in fast and accurate ways on future compact devices. This paper proposes an evaluation framework for realizing FPGA for cryptographic algorithms including DES, LED, TDES, AES-128, AES-192, and AES-256 with a symmetric key for both encipher and decipher. The framework is evaluated for its performance metrics of the area, operating frequency and power by hardware prototype architecture for these algorithms on Artix-7 FPGA device. The comparative analysis is presented for these metrics to get insights of its effectiveness on FPGA.

关键词： AES DES LED TDEA FPGA security S-Box Encryption Decryption

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Distributed system for multiple camera tracking

Distributed system for multiple camera tracking

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2011 12th IEEE International conference on multimedia and Expo, ICME 2011

作者： Leman, Karianto N.T., Pham R., Chang C., Wirianto I., Pek Institute for Infocomm Research Singapore

ISBN: (纸本)9781612843490

In practical surveillance applications, methods for multiple camera tracking have to deal with many challenges such as noises and errors in estimating system parameters. In this paper, we propose a distributed multiple camera tracking system that can track multiple persons in real time under challenging conditions such as inaccuracy from calibration, noises from background and lighting changes. The system combines a network of cameras located around the environment, a central process unit and mobile devices. Experimental results show that our system has already performed well in military training. © 2011 IEEE.

关键词： security systems

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Proceedings of International conference on Advanced Computing applications 1

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丛书名： Advances in Intelligent Systems and Computing

1000年

作者： Jyotsna Kumar Mandal Rajkumar Buyya Debashis De

ISBN: (数字)9789811652073

ISBN: (纸本)9789811652066

This book gathers selected high-quality research papers presented at the 2nd International conference on Advanced Computing applications (ICACA 2021), held virtually during 27––28 March 2021. The book is divided into four sections. These are communication and computing, signal processing and multimedia, computational intelligence and data analytics and decision computing. The topics covered are advanced communication technologies, IoT-based systems and applications, network security and reliability, virtualization technologies, compressed sensors and multimedia applications, signal image and video processing, machine learning, pattern recognitions, intelligent computing, big data analytics, analytics in bio-computing, AI-driven 6G mobile wireless networks and autonomous driving.

关键词： Computational Intelligence Artificial Intelligence Signal, image and Speech processing Communications Engineering, Networks Cyber-physical systems, IoT Professional Computing

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Study on the Method of Adversarial Example Attack Based on MI-FGSM 17th

Study on the Method of Adversarial Example Attack Based on M...

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17th International conference on Intelligent Information Hiding and multimedia Signal processing (IIH-MSP) / 14th International conference on Frontiers of Information Technology, applications and Tools (FITAT)

作者： Mao, Guanqiao Li, Lu Wang, Qingyu Li, Junbao Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Peoples R China Def Ind Secrecy Examinat & Certificat Ctr Beijing 100089 Peoples R China

ISBN: (纸本)9789811910579;9789811910562

Deep neural network outperformed human beings in many fields such as image classification [1-3], object detection [4, 5], and image semantic segmentation [6] in recent years. But this model has security risks;for instance, it can be considered as a black box and can hardly change to improve its performance when the training is complete, nobody is able to explain the exact meaning of the weights of a model. Those fatal flaws above produce a real problem, deep neural network is vulnerable and will be attacked by adversarial examples [7-9]. In this paper, we use MI-FGSM algorithm on three typical convolution neural network and produce three sets of adversarial example. Then we use these three sets of adversarial examples to attack three typical convolutional neural networks mentioned above, called white box attack. Next, we train three new convolutional neural network and attack them, called black box attack. The attack described above at military target dataset has a significant effect.

关键词： Adversarial example attack Convolutional neural network military targets Misclassification

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CAMFNet: A Context-Aware Multiscale Fusion Network for Enhanced Multispectral image Fusion in Remote Sensing and security 4

CAMFNet: A Context-Aware Multiscale Fusion Network for Enhan...

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4th International conference on multimedia processing, Communication and Information Technology, MPCIT 2024

作者： Suneel, J.S. Dileep, M.R. Visvesvaraya Technological University Nitte Meenakshi Institute of Technology Department of Master of Computer Applications Bengaluru India Nitte Meenakshi Institute of Technology Department of Master of Computer Applications Bengaluru India

ISBN: (数字)9798350375466

ISBN: (纸本)9798350375466

This research is mainly concerned with enhancing the object recognition and classification of multispectral imagery imagery especially of people and vehicles in the heavily vegetated regions. Sub-technology such as PCA and WT have inherent limit with regards to the ability to preserve both spatial and spectral properties. To fill the above-mentioned gaps, this work presents a CAMFNet;a framework that integrates multiscale fusion together with Visible (VIS), Near-Infrared (NIR) and Thermal Infrared (TIR) data for fusion and feature extraction and classification. CAMFNet uses classifiers like Gradient Tree Boost and SVM for differentiating people, cars, trees and other such objects. Feature extraction is carried out using PCA and HOG for enhancing the methods prior to the extraction. One of the radical innovations is the employment of certain aspects in CAMFNet, including multiscale feature extraction and attention mechanisms for boosted data fusion. The framework also involves generative aerial networks (GANs) and it is capable of preserving important spatial and spatial details profiles thereby making it to be more accurate, to more recalls and has low false positives compared to normal methods. Experiments made on real-world datasets coming from different landscapes, revealed that the CAMFNet outperformed the other networks in the classification metrics, as well as in PSNR and SSIM. Surveillance, agriculture, and the military are some of its uses to emphasize work in large-scale and distant investigations. It pushes the state-of-art in multispectral image fusion with this strong, scalable, real-time method for nonmilitary and military domains for large-scale objects recognition. © 2024 IEEE.

关键词： image fusion

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Complex Event processing for Content-Based Text, image, and Video Retrieval

Complex Event Processing for Content-Based Text, Image, and ...

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International conference on military Communications and Information Systems (ICMCIS)

作者： Bowman, Elizabeth K. Broome, Barbara D. Holland, V. Melissa Summers-Stay, Douglas Rao, Raghuveer M. Duselis, John Howe, Jonathan Madahar, Bhopinder K. Boury-Brisset, Anne-Claire Forrester, Bruce Kwantes, Peter Burghouts, Gertjan van Huis, Jasper Mulayim, Adem Yasar US Army Res Lab Computat & Informat Sci Directorate Dayton OH 45433 USA US Army Res Lab Sensors & Elect Devices Directorate Dayton OH 45433 USA US Army Res Lab Dayton OH 45433 USA UK Def Sci & Technol Lab Salisbury Wilts England Def Res & Dev Canada Valcartier PQ Canada Def Res & Dev Canada Toronto ON Canada TNO The Hague Netherlands Atos Turkey Ankara Turkey

ISBN: (纸本)9781509017775

This report summarizes the findings of an exploratory team of the North Atlantic Treaty Organization (NATO) Information Systems Technology panel into Content-Based Analytics (CBA). The team carried out a technical review into the current status of theoretical and practical developments of methods, tools and techniques supporting joint exploitation of multimedia data sources. In particular, content-based information retrieval and analytics was considered as a means to allow military experts to exploit multiple data sources in a rapid fashion for sensemaking and knowledge generation. Elements included contextual understanding of complex events through computational/human processing techniques, event prediction through the automated extraction of network features, temporal trends, hidden clusters and resource flows, and the use of machine processing for automated translation, parsing, information extraction, and summarization of unstructured and semistructured data. The main conclusions of the study are that important research gaps exist in all the technical areas covered in this report. Though the research areas and developments are being advanced in the military sector and the civil sector, in particular, they remain at low levels of technical maturity for defense and security system applications. It is recommended that NATO collaborative research effort be expanded to advance those approaches that are most pertinent to our overall aim of enhancing the contextual understanding of complex events through CBA of heterogeneous multimedia streams.

关键词： content-based analytics multimedia data sources sensemaking knowledge generation event prediction

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Biometric Jammer: A Prevention of Fake Acquisition of Fngerprint for security Enhancement. 1

Biometric Jammer: A Prevention of Fake Acquisition of Fngerp...

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1st International conference on Emerging Trends in Information Technology and Engineering, ic-ETITE 2020

作者： Deshmukh, Priya Mohod, Sharad Ram Meghe Institute of Technology Research Research Scholar Badnera-Amravati India

ISBN: (纸本)9781728141428

Biometric is a powerful tool use for the security in various domains such as mobile device security, law enforcement fields, civilian applications and military application. As the biometric has advantages properties and its wide application in various domains make it more popular also help to capture the commercial market. Even though the biometric system has to face the most common problem like is a spoofing attack and acquisition of biometric data. To detect and solve such attack problems involves use of a fake and liveness detection techniques in the system. Also to prevent the acquisition of image as it is the biometric valuable asset. The novel approach is put forward which suggested the use of fingerprint and palmprint as biometric data in the image form. The biometric data is pre-process and the further processing involves use of random forest classifier for the security enhancement and jam the spoofing attack on biometric system and asset. © 2020 IEEE.

关键词： Decision trees

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mobile visual object identification: from SIFT-BoF-RANSAC to SketchPrint

Mobile visual object identification: from SIFT-BoF-RANSAC to...

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conference on Media Watermarking, security, and Forensics

作者： Voloshynovskiy, Sviatoslav Diephuis, Mauritis Holotyak, Taras Univ Geneva Dept Comp Sci CH-1227 Carouge GE Switzerland

ISBN: (纸本)9781628414998

mobile object identification based on its visual features find many applications in the interaction with physical objects and security. Discriminative and robust content representation plays a central role in object and content identification. Complex post-processing methods are used to compress descriptors and their geometrical information, aggregate them into more compact and discriminative representations and finally re-rank the results based on the similarity geometries of descriptors. Unfortunately, most of the existing descriptors are not very robust and discriminative once applied to the various contend such as real images, text or noise-like microstructures next to requiring at least 500-1'000 descriptors per image for reliable identification. At the same time, the geometric re-ranking procedures are still too complex to be applied to the numerous candidates obtained from the feature similarity based search only. This restricts that list of candidates to be less than 1'000 which obviously causes a higher probability of miss. In addition, the security and privacy of content representation has become a hot research topic in multimedia and security communities. In this paper, we introduce a new framework for nonlocal content representation based on Sketch Print descriptors. It extends the properties of local descriptors to a more informative and discriminative, yet geometrically invariant content representation. In particular it allows images to be compactly represented by 100 Sketch Print descriptors without being fully dependent on re-ranking methods. We consider several use cases, applying Sketch Print descriptors to natural images, text documents, packages and micro-structures and compare them with the traditional local descriptors.

关键词： Visualization Sensors Databases Information security Digital watermarking Transform theory Cell phones image compression Computer programming Feature extraction

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