197 research outputs found

    Landmark Based Audio Fingerprinting for Naval Vessels

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    This paper presents a novel landmark based audio fingerprinting algorithm for matching naval vessels' acoustic signatures. The algorithm incorporates joint time - frequency based approach with parameters optimized for application to acoustic signatures of naval vessels. The technique exploits the relative time difference between neighboring frequency onsets, which is found to remain consistent in different samples originating over time from the same vessel. The algorithm has been implemented in MATLAB and trialed with real acoustic signatures of submarines. The training and test samples of submarines have been acquired from resources provided by San Francisco National Park Association [14]. Storage requirements to populate the database with 500 tracks allowing a maximum of 0.5 Million feature hashes per track remained below 1GB. On an average PC, the database hash table can be populated with feature hashes of database tracks @ 1250 hashes/second achieving conversion of 120 seconds of audio data into hashes in less than a second. Under varying attributes such as time skew, noise and sample length, the results prove algorithm robustness in identifying a correct match. Experimental results show classification rate of 94% using proposed approach which is a considerable improvement as compared to 88% achieved by [17] employing existing state of the art techniques such as Detection Envelope Modulation On Noise (DEMON) [15] and Low Frequency Analysis and Recording (LOFAR) [16]

    U-Net and its variants for medical image segmentation: theory and applications

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    U-net is an image segmentation technique developed primarily for medical image analysis that can precisely segment images using a scarce amount of training data. These traits provide U-net with a very high utility within the medical imaging community and have resulted in extensive adoption of U-net as the primary tool for segmentation tasks in medical imaging. The success of U-net is evident in its widespread use in all major image modalities from CT scans and MRI to X-rays and microscopy. Furthermore, while U-net is largely a segmentation tool, there have been instances of the use of U-net in other applications. As the potential of U-net is still increasing, in this review we look at the various developments that have been made in the U-net architecture and provide observations on recent trends. We examine the various innovations that have been made in deep learning and discuss how these tools facilitate U-net. Furthermore, we look at image modalities and application areas where U-net has been applied.Comment: 42 pages, in IEEE Acces

    Recent Application in Biometrics

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    In the recent years, a number of recognition and authentication systems based on biometric measurements have been proposed. Algorithms and sensors have been developed to acquire and process many different biometric traits. Moreover, the biometric technology is being used in novel ways, with potential commercial and practical implications to our daily activities. The key objective of the book is to provide a collection of comprehensive references on some recent theoretical development as well as novel applications in biometrics. The topics covered in this book reflect well both aspects of development. They include biometric sample quality, privacy preserving and cancellable biometrics, contactless biometrics, novel and unconventional biometrics, and the technical challenges in implementing the technology in portable devices. The book consists of 15 chapters. It is divided into four sections, namely, biometric applications on mobile platforms, cancelable biometrics, biometric encryption, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Norman Poh. We deeply appreciate the efforts of our guest editors: Dr. Girija Chetty, Dr. Loris Nanni, Dr. Jianjiang Feng, Dr. Dongsun Park and Dr. Sook Yoon, as well as a number of anonymous reviewers

    Missouri alumnus, volume 078, number 01 (1989 Fall)

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    Air Force Institute of Technology Research Report 2011

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    This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

    Technological Leap, Statutory Gap, and Constitutional Abyss: Remote Biometric Identification Comes of Age

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    Federal interest in using facial recognition technology (“FRT”) to collect, analyze, and use biometric information is rapidly growing. Despite the swift movement of agencies and contractors into this realm, however, Congress has been virtually silent on the current and potential uses of FRT. No laws directly address facial recognition—much less the pairing of facial recognition with video surveillance—in criminal law. Limits placed on the collection of personally identifiable information, moreover, do not apply. The absence of a statutory framework is a cause for concern. FRT represents the first of a series of next generation biometrics, such as hand geometry, iris, vascular patterns, hormones, and gait, which, when paired with surveillance of public space, give rise to novel questions of law and policy. These technologies constitute what can be termed Remote Biometric Identification (“RBI”). That is, they give the government the ability to ascertain the identity (1) of multiple people, (2) at a distance, (3) in public space, (4) absent notice and consent, and (5) in a continuous and on-going manner. RBI fundamentally differs from what can be understood as Immediate Biometric Identification (“IBI”)--i.e., the use of biometrics to determine identity at the point of arrest, following conviction, or in conjunction with access to secure facilities. IBI, in contrast, tends to be focused (1) on a single individual, (2) close-up, (3) in relation either to custodial detention or in the context of a specific physical area related to government activity, (4) in a manner often involving notice and often consent, and (5) is a one-time or limited occurrence. The types of legal and policy questions raised by RBI significantly differ from those accompanying IBI. In the absence of a statutory framework, we are driven to Constitutional considerations, where the Court’s jurisprudence proves inadequate as a way of addressing the concerns that present in the realm of RBI. The Fourth Amendment’s guarantee to protection against unreasonable search and seizure and the probable cause requirement for the issuance of warrants; the Fifth Amendment’s right against self-incrimination; the First Amendment’s protection of speech and assembly; and the Fifth and Fourteenth Amendments’ due process protections fail to account for the way in which such measures fundamentally challenge the current norms. The article calls for Congressional action and a judicial framing commensurate with the threat posed by these new and emerging technologies

    Structuring Techlaw

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    Technological breakthroughs challenge core legal assumptions and generate regulatory debates. Practitioners and scholars usually tackle these questions by examining the impacts of a particular technology within conventional legal subjects — say, by considering how drones should be regulated under privacy law, property law, or the law of armed conflict. While individually useful, these siloed analyses mask the repetitive nature of the underlying questions and necessitate the regular reinvention of the regulatory wheel. An overarching framework — one which can be employed across technologies and across subjects — is needed.The fundamental challenge of tech-law is not how to best regulate novel technologies, but rather how to best address familiar forms of uncertainty in new contexts. Accordingly, we construct a three-part framework, designed to encourage a more thoughtful resolution of tech-law questions. It:(1) delineates the three types of tech-fostered legal uncertainty, which facilitates recognizing common issues;(2) requires a considered selection between permissive and precautionary approaches to technological regulation, given their differing distributive consequences; and(3) highlights tech-law-specific considerations when extending extant law, creating new law, or reassessing a legal regime.This structure emphasizes the possibility of considered and purposeful intervention in the iterative and co-constructive relationship between law and technology. By making it easier to learn from the rich history of prior dilemmas and to anticipate future issues, this framework enables policymakers, judges, and other legal actors to make more just and effective regulatory decisions going forward

    Senate Bills

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    Listing of Senate bills from the 2013 General Assembl

    Senate Bills

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    Listing of Senate bills from the 2013 General Assembl
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