564 research outputs found

    Micro-power Pulsed-Doppler Radar Clutter and Displacement Source Classification Dataset

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    This is the official dataset for the ACM BuildSys 2019 publication One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification. The training code for MSC-RNN can be found at https://github.com/dhruboroy29/MSCRNN Kindly cite this work as: @article{roy2019one, title={One Size Does Not Fit All: Multi-Scale, Cascaded RNNs for Radar Classification}, author={Roy, Dhrubojyoti and Srivastava, Sangeeta and Kusupati, Aditya and Jain, Pranshu and Varma, Manik and Arora, Anish}, journal={arXiv preprint arXiv:1909.03082}, year={2019} } </pre

    Ideas for rent: an overview of markets for technology

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    This article surveys some of the recent literature on technology markets, and summarizes its main issues and insights. We structure our analysis in three parts: the supply and demand of technology; the factors that condition the formation and growth of technology markets; industry structure and dynamic issues. In addition, we summarize some of the studies that have tried to document the size and growth of these markets. We find that the literature has focused mainly on the supply of technology, but several other aspects of these markets remain under-studied, including the demand for external technology, the role of uncertainty in technology markets, and the dynamic interaction between industry structure and the market for technology. Understanding these will illuminate whether markets for technology will continue to grow or remained confined to pockets of the economy. Copyright 2010 The Author 2010. Published by Oxford University Press on behalf of Associazione ICC. All rights reserved., Oxford University Press.

    Metrics for analytics and visualization of big data with applications to activity recognition

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    Activity recognition systems detect the hidden actions of an agent from sensor measurements made on the agents' actions and the environmental conditions. For such systems, metrics are important for both performance evaluation and visualization purposes. In this thesis, such metrics are developed and illustrated. For human activity recognition datasets, a reporting structure is described to visualize the metrics in a systematic manner. The other contribution of this thesis is to describe a visualization tool for estimating the orientation (attitude) of a rigid body from streaming motion sensor (accelerometer and gyroscope) data. A feedback particle filter (FPF) is implemented algorithmically to solve the estimation problem.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2018-05-01The student, Rohan Arora, accepted the attached license on 2016-04-25 at 10:47.The student, Rohan Arora, submitted this Thesis for approval on 2016-04-25 at 10:48.This Thesis was approved for publication on 2016-04-27 at 15:05.DSpace SAF Submission Ingestion Package generated from Vireo submission #9459 on 2016-07-07 at 14:17:57Made available in DSpace on 2016-07-07T21:18:02Z (GMT). No. of bitstreams: 2 ARORA-THESIS-2016.pdf: 2048739 bytes, checksum: f76095ae5ef05e4ce14c6b05ab503f5d (MD5) LICENSE.txt: 4208 bytes, checksum: e5888a1be6c205bee6e88396c3d3da15 (MD5) Previous issue date: 2016-04-27Embargo set by: Seth Robbins for item 93308 Lift date: 2018-07-07T21:18:16Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemLimited Restriction Lifted for Item 93308 on 2018-07-08T09:15:30Z

    A comparative overview of constitutional human rights protections

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    Currently Australia has no bill of rights, few express rights, and two failed referenda: there is simply no ‘rights culture’ in Australia. However Australians are clinging to the few guarantees enshrined by the framers and craftily created by the judiciary

    First generation Asian immigrants and mental health treatment

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    Any first generation immigrant has a hard time assimilating to life in a new country, and this holds true for the Asian population and their mental health (Arora et al., 2020). This project focused on what impacts mental health of first generation Asian immigrants.Research presentationFaculty Mentor: Dr. Kathy Andrese

    Trial by Jury in Australia and India

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    As outline in this paper, “the jury service should be seen as an ongoing constitution identity as being a juror is like being a voter or an elected official, whereby ordinary citizens are directly contributing the institutions of government.

    Towards automated classification of fine-art painting style: a comparative study

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    This thesis presents a comparative study of different classification methodologies for the task of fine-art genre classification. The problem of painting classification involves classifying new unknown paintings among different art genres. Two-level comparative study is performed for this classification problem. The first level reviews the performance of discriminative vs. generative models while the second level touches the features aspect of the paintings and compares Semantic-level features vs low-level and intermediate-level features present in the painting. Three models are studied and compared, namely - 1) A Discriminative model using a Bag-of-Words (BoW) approach; 2) A Generative model using BoW; 3) Discriminative model using Semantic-level features. Various experiments and techniques like Bag of Words model, Topic models and Classeme features are employed to get insights into potential of these automatic classification techniques for painting styles.M.S.Includes bibliographical referencesby Ravneet Singh Aror

    Cryopreservation of in vitro raised plant cell line

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    Image White Balance for Multi-Illuminant Scenes

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    Performing white-balance (WB) correction for scenes with multiple illuminants remains a challenging task in computer vision. Most previous methods estimate per-pixel scene illumination directly in the RAW sensor image space. Recent work explored an alternative fusion strategy, where a neural network fuses multiple white-balanced versions of the input image processed to sRGB using pre-defined white-balance settings. Inspired by this line of work, we present two contributions targeting fusion-based multi-illuminant WB correction. First, we introduce a large-scale multi-illumination dataset rendered from RAW images to support training fusion models and evaluation. The dataset comprises over 16,000 sRGB images with ground truth sRGB white-balance corrected images. Next, we introduce an attention-based architecture to fuse five white-balance settings. This architecture yields an improvement of up to 25% over prior work
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