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Research on Novel Image Classification Algorithm based on Multi-Feature Extraction and Modified SVM Classifier
2015
International Journal of Smart Home
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Explicit structure, for example, a priori embedded deep learning model, can effectively reduce the size of the network parameter space and reduce the local minima problem, which can more effectively solve ...
Concentrate hierarchical expression, that is, deep learning. ...
recognition, vehicle traffic scene in the field of traffic count, retrograde motion detection, license plate detection and recognition, and the Internet in the field of content-based image retrieval, ...
doi:10.14257/ijsh.2015.9.9.11
fatcat:uts5gfvg2ncdld6yfqs5ya2lr4
Dimensionality Reduction of SPD Data Based on Riemannian Manifold Tangent Spaces and Isometry
2021
Entropy
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Symmetric positive definite (SPD) data have become a hot topic in machine learning. Instead of a linear Euclidean space, SPD data generally lie on a nonlinear Riemannian manifold. ...
Then, we use it for the DR of original SPD data. Experiments on five commonly used datasets show that RMTSISOM-SPDDR is superior to five advanced SPD data DR algorithms. ...
Acknowledgments: The authors are grateful to Ting Gao for academic exchange and Sun Yat-sen University for the information supportive platform. ...
doi:10.3390/e23091117
pmid:34573742
fatcat:oedzhjynxrewxpc3ubn4c353bi
2021 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 32
2021
IEEE Transactions on Neural Networks and Learning Systems
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Departments and other items may also be covered if they have been judged to have archival value. The Author Index contains the primary entry for each item, listed under the first author's name. ...
The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
., +, TNNLS Sept. 2021 4217-4230 Gesture recognition Image Set Classification Using a Distance-Based Kernel Over Affine Grassmann Manifold. ...
doi:10.1109/tnnls.2021.3134132
fatcat:2e7comcq2fhrziselptjubwjme
Learning Neural Textual Representations for Citation Recommendation
2021
2020 25th International Conference on Pattern Recognition (ICPR)
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396 A General Framework for Small Object Detection Leveraging on Simultaneous Unsupervised Super-resolution Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data DAY 4 ...
Networks for Short-Term Highway Traffic Forecasting Ghost Target Detection in 3D Radar Data Using Point Cloud Based Deep Neural Network DAY 4 -Jan 15, 2021 Kocaman, Veysel; Shir, Ofer M.; Baeck, Thomas ...
doi:10.1109/icpr48806.2021.9412725
fatcat:3vge2tpd2zf7jcv5btcixnaikm
Towards an Intelligent Edge: Wireless Communication Meets Machine Learning
[article]
2018
arXiv
pre-print
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This article advocates a new set of design principles for wireless communication in edge learning, collectively called learning-driven communication. ...
Accordingly, a new research area, called edge learning, emerges, which crosses and revolutionizes two disciplines: wireless communication and machine learning. ...
A motion can be represented by a sequence of subspaces, which is translated into a trajectory on a Grassmann manifold. ...
arXiv:1809.00343v1
fatcat:somwcxfplzesfcmukcg6qjvcoq
2019 Index IEEE Robotics and Automation Letters Vol. 4
2019
IEEE Robotics and Automation Letters
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., +, LRA Oct. 2019 3852-3859 Deep Metadata Fusion for Traffic Light to Lane Assignment. ...
., +, LRA July 2019 2714-2721 Deep Metadata Fusion for Traffic Light to Lane Assignment. ...
Permanent magnets Adaptive Dynamic Control for Magnetically Actuated Medical Robots. ...
doi:10.1109/lra.2019.2955867
fatcat:ckastwefh5chhamsravandtnx4
A Comprehensive Survey on Transfer Learning
[article]
2020
arXiv
pre-print
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In order to show the performance of different transfer learning models, over twenty representative transfer learning models are used for experiments. ...
Due to the wide application prospects, transfer learning has become a popular and promising area in machine learning. ...
Transfer learning can also be utilized for anomalous activity detection [188] , [189] , traffic sign recognition [190] , etc. ...
arXiv:1911.02685v3
fatcat:oeofarz7tnbtlblvta4evx3e34
A Review of Single-Source Deep Unsupervised Visual Domain Adaptation
[article]
2020
arXiv
pre-print
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In this paper, we review the latest single-source deep unsupervised domain adaptation methods focused on visual tasks and discuss new perspectives for future research. ...
Domain adaptation is a machine learning paradigm that aims to learn a model from a source domain that can perform well on a different (but related) target domain. ...
[102] proposed a Manifold Embedded Distribution Alignment approach which learns a domain-invariant classifier in Grassmann manifold with structural risk minimization, while performing dynamic distribution ...
arXiv:2009.00155v3
fatcat:yqkew4n4q5gtbjosozufw37ome
Intelligent Computing Research Studies in Life Science
2019
International Journal of Pharma and Bio Sciences
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Thus, the principle point of this paper is to structure a remote framework that can analyse and give the patient fundamental suggestions on the LCD display screen, distinguish and report when out of range ...
The articles published in this special issue will certainly bring as positive effect for the developing health care and to make use of available resources and to remove certain obsolete factors and process ...
This framework used the face detection and recognition techniques. Then can evaluate the performance using accuracy metrics. ...
doi:10.22376/ijpbs/10.sp01/oct/2019.1-142
fatcat:6fc5ghwmjbgrphetiablavajxm
Towards a fourth spatial dimension of brain activity
2016
Cognitive Neurodynamics
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The opportunity to treat the nervous system as a topological structure makes BUT a universal principle underlying neural phenomena and brain function. ...
In particular, the Borsuk-Ulam Theorem (BUT) states that, if a single point projects to a higher spatial dimension, it gives rise to two antipodal points with matching description. ...
ACKNOWLEDGEMENTS The Authors would like to thank Norbert Jausovec for his precious comments. and let f : S d ®R d be a continuous map. ...
doi:10.1007/s11571-016-9379-z
pmid:27275375
pmcid:PMC4870410
fatcat:kgfvl25o6fcpfdiitcmvaumska
Non-IID data and Continual Learning processes in Federated Learning: A long road ahead
[article]
2021
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Federated Learning is a novel framework that allows multiple devices or institutions to train a machine learning model collaboratively while preserving their data private. ...
At the same time, we introduce approaches from other machine learning frameworks, such as Continual Learning, that also deal with data heterogeneity and could be easily adapted to the Federated Learning ...
Competitive Groups accreditation 2021-2024, ED431C 2018/29, ED431F2018/02 and ED431C 2021/30) and the European Union (European Regional Development Fund -ERDF). ...
doi:10.48550/arxiv.2111.13394
fatcat:iz7hqfpqgrhoro4eoohzotdwdq
ELECTRONIC SYSTEMS WITH HIGH ENERGY EFFICIENCY FOR EMBEDDED COMPUTER VISION
unpublished
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Lui et al. [66, 67] used tensors and tangent bundle on Grassmann manifolds to classify human actions and hand gestures. ...
For this purpose, we decided to use a machine learning stage that inputs the previous accumulators and learns the number of people from that data. ...
Elisa Ricci and Prof. Geoff Merrett that reviewed this Thesis for their precious advices. Particular to Dr. Giuseppe Serra, which patiently followed me during these years and to Lorenzo Baraldi. ...
fatcat:q2okfalyt5hohmomj3ajctbqiu
Deep Learning-Aided 6G Wireless Networks: A Comprehensive Survey of Revolutionary PHY Architectures
[article]
2022
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Deep learning (DL) has proven its unprecedented success in diverse fields such as computer vision, natural language processing, and speech recognition by its strong representation ability and ease of computation ...
Furthermore, this article provides programming examples for a number of DL techniques and the implementation of a DL-based MIMO by sharing user-friendly code snippets, which might be useful for interested ...
Each point on the Grassmann manifold is a unitary matrix, and the distance between each point pair equals the chordal Frobenius norm. ...
doi:10.48550/arxiv.2201.03866
fatcat:ibvzihwplrdvjphfsve6iu7vea
SIGNAL 2017 Committee SIGNAL Steering Committee SIGNAL 2017 Technical Program Committee
2017
China Narendra Kohli
unpublished
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We hope that SIGNAL 2017 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in the field of signal processing. ...
Having these motivations in mind, the goal of this conference was to bring together researchers and industry and form a forum for fruitful discussions, networking, and ideas. ...
ACKNOWLEDGEMENT This research is funded in part by grants from US National Science Foundation (NSF) [EAGER-1419055 and DGE-1439570]. ...
fatcat:lkia3ecskbbfpig5kmo5jkgcbm
Low-rank and Sparse based Representation Methods with the Application of Moving Object Detection
2019
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In this thesis, we study the problem of detecting moving objects from an image sequence using low-rank and sparse representation concepts. ...
Finally, I wish to express my deep gratitude to my parents for their neverending love and support along the way. ...
(a) We propose a robust representation of images against illumination, which is used in visual place recognition, classification, and change detection. ...
doi:10.7939/r3-naxk-bd56
fatcat:v57inhxs5vabbaui4omn7krhda
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