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A Survey on Metric Learning for Object Re-identification in Intelligent Surveillance

Yi Ping
2017 DEStech Transactions on Engineering and Technology Research  
To tackle the problem, metric learning has become an optimal method, and the approaches are concerned with learning a distance function tuned to a particular identification task, and have been shown to  ...  This paper provides a survey of existing metric learning approaches for object re-identification, which focuses on the methods based on the application of metric learning.  ...  Introduction Nowadays, object re-identification (Re-ID) has been more and more attractive in computer vision, which is due to the requirements of intelligent surveillance in different occasions.  ... 
doi:10.12783/dtetr/ismii2017/16644 fatcat:j4ocgyrsnbfjdkha7bv4uvr2xy


2001 International journal on artificial intelligence tools  
The paper presents an approach to inductive machine learning based on a consistent integration of the generalization-based (such as inductive learning from examples) and metric-based (such as agglomerative  ...  The approach stems from the natural idea (formally studied within lattice theory) to estimate the similarity between two objects in a hierarchical structure by the distances to their closest common parent  ...  Acknowledgments Many thanks to the anonymous referees for the valuable comments and suggestions that improved the paper.  ... 
doi:10.1142/s0218213001000519 fatcat:43dk2esqzrc2dp4opsfekrh34y

Intelligent Surveillance Systems: A Review

Jose Manuel Mejia Muñoz, Adrián Mariscal Torres, Leticia Ortega Máynez
2020 Cultura científica y tecnológica  
We have also seen that, in terms of security, deep learning is highly viable to solve problems that have been implicit in security systems for a long time, this being able to turn deep learning into a  ...  This research offers a literature review about security subject, focused on autonomous surveillance, gathering in a single document the technical novelties about surveillance systems, their applications  ...  Metrics for machine learning-based algorithms In this section, we review the metrics to quantify the performance of the various algorithms specialized in people-oriented detection and identification of  ... 
doi:10.20983/culcyt.2020.2.3.1 fatcat:i5xgv5hc5zbzface27ilu46cfy

An Interactive Tool for Human Active Learning in Constrained Clustering

Masayuki Okabe, Seiji Yamada
2011 Journal of Emerging Technologies in Web Intelligence  
Moreover, it can be used to execute distance metric learning and k-means clustering.  ...  In this paper, we show an overview of the tool and how it works, especially for the functions for display arrangement by using multi-dimensional scaling and incremental distance metric learning.  ...  Then, we describe the two main functions of the tool -display arrangement by multi-dimensional scaling and incremental distance metric learning, in Sections 3 and 4.  ... 
doi:10.4304/jetwi.3.1.20-27 fatcat:hzx7q64fqnfzhdfg32lkuuycia

Guest Editorial Introduction to the Special Section on Intelligent Visual Content Analysis and Understanding

Hongliang Li, Lu Fang, Tianzhu Zhang
2020 IEEE transactions on circuits and systems for video technology (Print)  
Guest Editorial Introduction to the Special Section on Intelligent Visual Content Analysis and Understanding V ISUAL content analysis and understanding attract tremendous attention because of its potentially  ...  As entering the deep learning era, various powerful deep neural networks further enable an intelligent vision system to cope with more complex scenarios.  ... 
doi:10.1109/tcsvt.2020.3031416 fatcat:gpwbmydqbza5lddatxcfcidwcq

Data-driven Intelligence System for General Recommendations of Deep Learning Architectures

Gjorgji Noveski, Tome Eftimov, Kostadin Mishev, Monika Simjanoska
2021 IEEE Access  
Natural language processing (NLP) methods are used to create structured data from unstructured scientific papers upon which intelligent models are learned to propose optimal DL architecture, layer type  ...  The most common approach relies on popular architectures proven to work on specific problem domains led on the same experiment environment and setup.  ...  LEARNING THE INTELLIGENT MODELS The process for learning the intelligent systems consists of three main steps as shown in the "Learning intelligent system" section of Figure 1 .  ... 
doi:10.1109/access.2021.3124633 fatcat:zs36wcot2bab5bgdblj76ezo7a

Giving Neurons to Sensors: An Approach to QoS Management Through Artificial Intelligence in Wireless Networks [chapter]

Julio Barbancho, Carlos León, Javier Molina, Antonio Barbancho
2006 Lecture Notes in Computer Science  
on the introduction of neural networks in every sensor node.  ...  Due to the constraints on data processing and power consumption, the use of artificial intelligence has been historically discarded.  ...  Our approach to enhance this solution is based on the introduction of artificial intelligence techniques in the WSNs: expert systems, artificial neural networks, fuzzy logic and genetic algorithms.  ... 
doi:10.1007/11872153_30 fatcat:lv4cgtjsnvgelmpisx5dbyipve

Kanji Workbook: A Writing-Based Intelligent Tutoring System for Learning Proper Japanese Kanji Writing Technique with Instructor-Emulated Assessment

Paul Taele, Jung In Koh, Tracy Hammond
We introduce Kanji Workbook, a writing-based intelligent tutoring system for students to receive intelligent assessment that emulates human instructor feedback.  ...  Our interface not only leverages students' computing devices for allowing them to learn, practice, and review the writing of prompted characters from their course's kanji script lessons, but also provides  ...  Acknowledgements We give our huge thanks to instructors George Adams and Yuki Waugh at Texas A&M University for their valuable assistance in providing consultation on our interface and access to their  ... 
doi:10.1609/aaai.v34i08.7053 fatcat:hj4qy4rhwjfwjashnaeesrfhiy

Evaluation Mechanism of Collective Intelligence for Heterogeneous Agents Group [article]

Anna Dai, Zhifeng Zhao, Honggang Zhang, Rongpeng Li, Yugeng Zhou
2019 arXiv   pre-print
The intelligence level of heterogeneous agents groups is compared with the homogeneous ones to analyze the effects of heterogeneity on collective intelligence.  ...  Our work will help to understand the essence of collective intelligence more deeply and reveal the effect of various key factors on group intelligence level.  ...  Kannan and Parker [7] proposed an effective metric for the evaluation of learning capability. They attempt to evaluate the quality of learning towards understanding system level fault-tolerance.  ... 
arXiv:1903.00206v2 fatcat:srdhsafranhlxawhzq6w6eikzq

Guest Editorial: Introduction to the Special Section on Intelligence-Empowered Collaboration Among Space, Air, Ground, and Sea Mobile Networks Towards B5G

Liang Zhao, Neeraj Kumar, Celimuge Wu, Jia Hu, Ahmed Al-Dubai
2021 IEEE Transactions on Network Science and Engineering  
This special section is one of the first publication venues focusing on this timely topic. We intend to foster innovative work that employs AI to design new techniques in B5G-SAGS.  ...  In this special section, Deb et al. in "XiA: Send-it-Anyway Q-Routing for 6G-Enabled UAV-LEO Communications" propose Q-Learningbased routing algorithm, namely, XiA, by involving UAVs to send the data to  ...  UAV-Ground: In this special section, the UAV-Ground related topic has been studied in four aspects.  ... 
doi:10.1109/tnse.2021.3109386 fatcat:d2c2cal2wvhl7mbvbvcxndpbha

MetrIntSimil—An Accurate and Robust Metric for Comparison of Similarity in Intelligence of Any Number of Cooperative Multiagent Systems

Laszlo Iantovics, Matthias Dehmer, Frank Emmert-Streib
2018 Symmetry  
systems specialized in difficult problem solving.  ...  It allows a classification of the cooperative multiagent systems based on their similarity in intelligence.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/sym10020048 fatcat:v6sboxerxffwro6c3blf7a3zqe

Introduction to the Special Issue on Nature-Inspired Optimization Methods in Fuzzy Systems

Adam Slowik, Krzysztof Cpalka, Yaochu Jin
2020 IEEE transactions on fuzzy systems  
Introduction to the Special Issue on Nature-Inspired Optimization Methods in Fuzzy Systems I.  ...  We will give a brief introduction to the articles presented in this special issue according to the aforementioned four categories. II.  ...  Yaochu Jin (Fellow, IEEE) received the B.Sc., M.Sc., and Ph.D. degrees automatic control from Zhejiang University, Hangzhou, China, in 1988 , 1991 , and 1996, respectively, and  ... 
doi:10.1109/tfuzz.2020.2983712 fatcat:3xvjzkaagvernkwv4zs3xsptfy

An intelligent framework for end‐to‐end rockfall detection

Thanasis Zoumpekas, Anna Puig, Maria Salamó, David Garcı́a‐Sellés, Laura Blanco Nuñez, Marta Guinau
2021 International Journal of Intelligent Systems  
In particular, we propose an intelligent system that utilizes multiple machine learning algorithms to detect rockfall clusters of point cloud data.  ...  This paper addresses this issue and provides an intelligent framework for rockfall event detection for any individual working in the intersection of the geology domain and decision support systems.  ...  K E Y W O R D S geology, imbalanced classification, intelligent systems, machine learning, rockfall monitoring | INTRODUCTION In the field of geology, one crucial task is rockfall detection, which helps  ... 
doi:10.1002/int.22557 fatcat:3rkouluwfjazzgrpks53qu6gse

Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes

Pablo Samuel Castro
We then present two new algorithms for approximating bisimulation metrics in large, deterministic MDPs. The first does so via sampling and is guaranteed to converge to the true metric.  ...  In this paper we present a new version of the metric that is tied to a behavior policy in an MDP, along with an analysis of its theoretical properties.  ...  Machado, Doina Precup, Carles Gelada, as well as the rest of the Google Brain team in Montreal for helpful discussions.  ... 
doi:10.1609/aaai.v34i06.6564 fatcat:bopjae4ddfcgdirjbgtirug4ja

II-Learn—A Novel Metric for Measuring the Intelligence Increase and Evolution of Artificial Learning Systems

László Barna Iantovics, Dimitris K. Iakovidis, Elena Nechita
2019 International Journal of Computational Intelligence Systems  
To prove the effectiveness of the metric we performed a case study, using a learning system.  ...  A B S T R A C T A novel accurate and robust metric called II-Learn for measuring the increase of intelligence of a system after a learning process is proposed.  ...  ACKNOWLEDGMENTS This work was supported by the project CNFIS-FDI-2019-0453: Support actions for excellence in research, innovation and technological transfer at "Vasile Alecsandri" University of Bacău  ... 
doi:10.2991/ijcis.d.191101.001 fatcat:k3nalalqezcobbx4zl4333ev4m
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