ScienceGate
Advanced Search
Author Search
Journal Finder
Blog
Sign in / Sign up
ScienceGate
Search
Author Search
Journal Finder
Blog
Sign in / Sign up
Anomaly Detection in Image Datasets Using Convolutional Neural Networks, Center Loss, and Mahalanobis Distance
2021 Ural Symposium on Biomedical Engineering, Radioelectronics and Information Technology (USBEREIT)
◽
10.1109/usbereit51232.2021.9455004
◽
2021
◽
Author(s):
Garnik Vareldzhan
◽
Kirill Yurkov
◽
Konstantin Ushenin
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Mahalanobis Distance
◽
Center Loss
◽
Image Datasets
Download Full-text
Related Documents
Cited By
References
Unsupervised Hyperspectral Anomaly Detection with Convolutional Neural Networks
2021 29th Signal Processing and Communications Applications Conference (SIU)
◽
10.1109/siu53274.2021.9477870
◽
2021
◽
Author(s):
Fatma Nur Yilmaz
◽
Sertac Arisoy
◽
Koray Kayabol
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Convolutional Neural Networks
Download Full-text
Machine learning-based climate time series anomaly detection using convolutional neural networks
Weather and Climate
◽
10.2307/27031377
◽
2020
◽
Vol 40
(1)
◽
pp. 16
Author(s):
Srinivasan
◽
Wang
◽
Bulleid
Keyword(s):
Machine Learning
◽
Neural Networks
◽
Time Series
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Climate Time Series
Download Full-text
Constrained Center Loss for Convolutional Neural Networks
IEEE Transactions on Neural Networks and Learning Systems
◽
10.1109/tnnls.2021.3104392
◽
2021
◽
pp. 1-9
Author(s):
Zhanglei Shi
◽
Hao Wang
◽
Chi-Sing Leung
Keyword(s):
Neural Networks
◽
Convolutional Neural Networks
◽
Center Loss
Download Full-text
Convolutional Neural Networks for Unsupervised Anomaly Detection in Text Data
Lecture Notes in Computer Science - Intelligent Data Engineering and Automated Learning – IDEAL 2017
◽
10.1007/978-3-319-68935-7_54
◽
2017
◽
pp. 500-507
◽
Cited By ~ 2
Author(s):
Oleg Gorokhov
◽
Mikhail Petrovskiy
◽
Igor Mashechkin
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Text Data
◽
Unsupervised Anomaly Detection
Download Full-text
Radio Frequency Classification and Anomaly Detection using Convolutional Neural Networks
2019 IEEE Radar Conference (RadarConf)
◽
10.1109/radar.2019.8835662
◽
2019
◽
Cited By ~ 2
Author(s):
Marvin A. Conn
◽
Darsana Josyula
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Radio Frequency
◽
Convolutional Neural Networks
Download Full-text
An Empirical Study on Network Anomaly Detection Using Convolutional Neural Networks
2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)
◽
10.1109/icdcs.2018.00178
◽
2018
◽
Cited By ~ 17
Author(s):
Donghwoon Kwon
◽
Kathiravan Natarajan
◽
Sang C. Suh
◽
Hyunjoo Kim
◽
Jinoh Kim
Keyword(s):
Neural Networks
◽
Empirical Study
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Network Anomaly Detection
Download Full-text
Anomaly detection using 1D convolutional neural networks for surface enhanced raman scattering
SPIE Future Sensing Technologies
◽
10.1117/12.2576447
◽
2020
◽
Author(s):
M. Hamed Mozaffari
◽
Li-Lin Tay
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Raman Scattering
◽
Convolutional Neural Networks
◽
Surface Enhanced Raman Scattering
◽
Surface Enhanced
◽
Surface Enhanced Raman
◽
Enhanced Raman Scattering
Download Full-text
Feature Extraction Using Convolutional Neural Networks for Anomaly Detection
Anais do 14. Congresso Brasileiro de Inteligência Computacional
◽
10.21528/cbic2019-7
◽
2020
◽
Author(s):
Rodrigo de Paula Monteiro
◽
Carmelo José Albanez Bastos Filho
Keyword(s):
Neural Networks
◽
Feature Extraction
◽
Anomaly Detection
◽
Convolutional Neural Networks
Download Full-text
Two Stream Convolutional Neural Networks for Anomaly Detection in Surveillance Videos
Advances in Intelligent Systems and Computing - Smart Computing Paradigms: New Progresses and Challenges
◽
10.1007/978-981-13-9683-0_5
◽
2019
◽
pp. 41-48
Author(s):
Adarsh Jamadandi
◽
Sunidhi Kotturshettar
◽
Uma Mudenagudi
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Surveillance Videos
Download Full-text
A Feature Compression Technique for Anomaly Detection Using Convolutional Neural Networks
2020 IEEE 14th International Conference on Anti-counterfeiting, Security, and Identification (ASID)
◽
10.1109/asid50160.2020.9271685
◽
2020
◽
Author(s):
Shuyong Liu
◽
Hongrui Jiang
◽
Sizhao Li
◽
Yang Yang
◽
Linshan Shen
Keyword(s):
Neural Networks
◽
Anomaly Detection
◽
Convolutional Neural Networks
◽
Compression Technique
Download Full-text
Sign in / Sign up
Close
Export Citation Format
Close
Share Document
Close