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Joint Noise-Tolerant Learning and Meta Camera Shift Adaptation for Unsupervised Person Re-Identification

Fengxiang Yang, Zhun Zhong, Zhiming Luo, Yuanzheng Cai, Yaojin Lin, Shaozi Li, Nicu Sebe
2021 Zenodo  
This paper considers the problem of unsupervised person re-identification (re-ID), which aims to learn discriminative models with unlabeled data.  ...  Concretely, we propose a Dynamic and Symmetric Cross Entropy loss (DSCE) to deal with noisy samples and a camera-aware meta-learning algorithm (MetaCam) to adapt camera shift.  ...  Related Work Unsupervised Person Re-ID Unsupervised person re-ID can be categorized into Fully Unsupervised Re-ID (FU) [19, 20, 42] and Unsupervised Domain Adaptation (UDA) [49, 41, 18, 24] .  ... 
doi:10.5281/zenodo.5014558 fatcat:hm4mo4jpandvfk2jfeq2sh26b4

2020 Index IEEE Transactions on Image Processing Vol. 29

2020 IEEE Transactions on Image Processing  
., +, TIP 2020 8429-8442 Unsupervised Person Re-identification via Cross-Camera Similarity Exploration.  ...  Rong, X., +, TIP 2020 591-601 Unsupervised Person Re-identification via Cross-Camera Similarity Exploration.  ... 
doi:10.1109/tip.2020.3046056 fatcat:24m6k2elprf2nfmucbjzhvzk3m

Deep Speaker Recognition: Process, Progress, and Challenges

Abu Quwsar Ohi, M. F. Mridha, Md. Abdul Hamid, Muhammad Mostafa Monowar
2021 IEEE Access  
Though speaker recognition systems were previously constructed using handcrafted statistical means of machine learning, currently it is being shifted to state-of-the-art deep learning strategies.  ...  Speaker recognition is related to human biometrics dealing with the identification of speakers from their speech.  ...  Call centers can also inherit speaker re-identification for personalized services and queries.  ... 
doi:10.1109/access.2021.3090109 fatcat:klq443bqmjh4vakpfvwqelujvi

Sparse Camera Network for Visual Surveillance -- A Comprehensive Survey [article]

Mingli Song, Dachent Tao, Stephen J. Maybank
2013 arXiv   pre-print
In this review paper, we present a comprehensive survey of recent research results to address the problems of intra-camera tracking, topological structure learning, target appearance modeling, and global  ...  A sparse camera network undertakes large area surveillance using as few cameras as possible, and most cameras have non-overlapping fields of view with one another.  ...  c) Newly defined global descriptors for human re-identification: Gandhi et al.  ... 
arXiv:1302.0446v1 fatcat:j3opbzuaw5eb3c74c2ind5pmua

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Unsupervised Person Re-identification DAY 4 -Jan 15, 2021 Dietlmeier, Julia; Antony, Joseph; McGuinness, Kevin; O'Connor, Noel E 1921 How Important Are Faces for Person Re-Identification?  ...  Domain Adaptation for Image-Based Person Re-Identification DAY 2 -Jan 13, 2021 Liu, Xiyao; Ma, Ziping; Guo, Xingbei; Hou, Jialu; Wang, Lei; Schaefer, Gerald; Fang, Hui 2129 Joint Compressive  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

Towards Robust Pattern Recognition: A Review [article]

Xu-Yao Zhang, Cheng-Lin Liu, Ching Y. Suen
2020 arXiv   pre-print
Actually, our brain is robust at learning concepts continually and incrementally, in complex, open and changing environments, with different contexts, modalities and tasks, by showing only a few examples  ...  directions for robust pattern recognition.  ...  For large-scale dataset cleaning, the partitioning filter [339] is proposed for noise identification from large distributed datasets.  ... 
arXiv:2006.06976v1 fatcat:mn35i7bmhngl5hxr3vukdcmmde

Unsupervised human activity analysis for intelligent mobile robots

Paul Duckworth, David C. Hogg, Anthony G. Cohn
2019 Artificial Intelligence  
In this thesis an approach for unsupervised learning of activities implemented on an autonomous mobile robot is presented.  ...  This allows the mobile robot to efficiently learn and update its models of human activity over time, discarding the raw data, allowing for life-long learning.  ...  This gives the robot an estimated position of a person relative to the map and invariant to visual noise which often affects camera systems, e.g. lighting or motion variabilities.  ... 
doi:10.1016/j.artint.2018.12.005 fatcat:vq56rrsuojfq3kzr3ip3tj4d74

Vision-based human activity recognition: a survey

Djamila Romaissa Beddiar, Brahim Nini, Mohammad Sabokrou, Abdenour Hadid
2020 Multimedia tools and applications  
Although several extensive review papers have already been published in the general HAR topics, the growing technologies in the field as well as the multi-disciplinary nature of HAR prompt the need for  ...  At the same time, it will highlight the main challenges and future directions.  ...  Acknowledgments The authors wish to thank Prof Mourad Oussalah from the center for machine vision and signal analysis, university of Oulu, who participated in writing and technical editing of the manuscript  ... 
doi:10.1007/s11042-020-09004-3 fatcat:f5n7xop4vveannwcvw47ewhsrq

2020 Index IEEE Transactions on Vehicular Technology Vol. 69

2020 IEEE Transactions on Vehicular Technology  
+ Check author entry for coauthors ami-mFading Channels With Integer and Non-Integerm; TVT March 2020 2785-2801 Hoang, T.M., Tran, X.N., Nguyen, B.C., and Dung, L.T., On the Performance of MIMO Full-Duplex  ...  Yu, X., A Joint Design of Platoon Communication and Control Based on LTE-V2V; 15893-15907 Hong, C.S., see Nguyen, M.N.H., TVT May 2020 5618-5633 Hong, C.S., see Chen, D., TVT May 2020 5634-5646 Hong  ...  ., +, Connected Vehicle Based Distributed Meta-Learning for Online Adaptive Engine/Powertrain Fuel Consumption Modeling.  ... 
doi:10.1109/tvt.2021.3055470 fatcat:536l4pgnufhixneoa3a3dibdma

Deep Learning in Mobile and Wireless Networking: A Survey [article]

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 arXiv   pre-print
Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.  ...  The recent success of deep learning underpins new and powerful tools that tackle problems in this space.  ...  , meta heuristics).  ... 
arXiv:1803.04311v3 fatcat:awuvyviarvbr5kd5ilqndpfsde

Deep Learning in Mobile and Wireless Networking: A Survey

Chaoyun Zhang, Paul Patras, Hamed Haddadi
2019 IEEE Communications Surveys and Tutorials  
Drawing from our experience, we discuss how to tailor deep learning to mobile environments. We complete this survey by pinpointing current challenges and open future directions for research.  ...  The recent success of deep learning underpins new and powerful tools that tackle problems in this space.  ...  , meta heuristics).  ... 
doi:10.1109/comst.2019.2904897 fatcat:xmmrndjbsfdetpa5ef5e3v4xda

Analytical Methods for Detection of Plant Metabolomes Changes in Response to Biotic and Abiotic Stresses

Anna Piasecka, Piotr Kachlicki, Maciej Stobiecki
2019 International Journal of Molecular Sciences  
in successful breeding of stress tolerant or resistant crop plants.  ...  Metabolomics based on mass spectrometric techniques is an important part of research conducted in the direction of breeding new varieties of crop plants tolerant to the affecting stresses and possessing  ...  In addition, it facilitates integration to other "omics" by biomarker meta-analysis, joint pathway analysis, and network explorer module.  ... 
doi:10.3390/ijms20020379 fatcat:xhwo2gbg55cavh6zvgbhnygnd4

Deep Reinforcement Learning [article]

Yuxi Li
2018 arXiv   pre-print
Then we discuss important mechanisms for RL, including attention and memory, unsupervised learning, hierarchical RL, multi-agent RL, relational RL, and learning to learn.  ...  We start with background of artificial intelligence, machine learning, deep learning, and reinforcement learning (RL), with resources.  ...  The authors propose policy-space response oracle (PSRO), and its approximation, deep cognitive hierarchies (DCH), to compute best responses to a mixture of policies using deep RL, and to compute new meta-strategy  ... 
arXiv:1810.06339v1 fatcat:kp7atz5pdbeqta352e6b3nmuhy

Visual analysis of faces with application in biometrics, forensics and health informatics [article]

Mohammad Ahsanul Haque
2016 Ph.d.-serien for Det Teknisk-Naturvidenskabelige Fakultet, Aalborg Universitet  
Several machine learning approaches were also proposed for detection and identification of falls [241] , [242] , [91], [243] , [92] , which help to minimize those false alarms by automatically adapting  ...  Unsupervised and supervised learning is often used in conjunction, when clustering results serve as an extra input for classification, as for example in [286] , [443] .  ...  For example, fingerprint and hand-written signature can be forged to breach the identification system [2] , voice can be altered or imitated, and still picture based traits can be used in absence of the  ... 
doi:10.5278/ fatcat:445elv6ftfcw3lhg7svwqx3ifu


2021 2021 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)  
This motivated the need for new emerging trends such as Edge, Fog, and Pervasive Computing, where we merge hierarchical computing with efficient communication, leveraging learning-based distributed optimization  ...  He is serving as a technical editor for international journals and has served as a technical program committee (TPC) co-chair for many IEEE conferences and workshops.  ...  This paper discusses a new model of digital twins suitable not only for industries but for personalized education and life-long learning.  ... 
doi:10.1109/ccece53047.2021.9569199 fatcat:35c7o6f6svc5rgnyhjpbvjp7iy
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