지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2018.10
- 수록면
- 661 - 665 (5page)
이용수
초록· 키워드
오류제보하기
Unsupervised visual anomaly detection is currently one of the most challenging machine learning problems. Various techniques have been specifically developed for certain limited domains while some are more generic towards a broader scope of applications. This paper aims to investigate a novel solution for general anomaly detection in surveillance videos by modeling patterns and objects that appear normally in the videos and then using this model to detect the anomalous objects by exploiting image reconstruction methodologies. This approach is inspired by the recent progression in development of robust semantic in-painting techniques. For our experiments, Context Encoders are used for the said purpose. Context encoders are proven successful to reconstruct missing holes in images based on the non-hole parts. Our proposed methodology is semi-supervised which means it does not require an annotated dataset however the videos of cases containing normal scenes are required separately to train the system. Various experiments suggest that the proposed methodology can successfully locate potentially anomalous images from the normal ones. This paper discusses in depth the possibilities of adopting such systems for general anomaly detection, pros, cons as well as the limitations of the overall methodology.
목차
Abstract
1. INTRODUCTION
2. DATASET
3. ARCHITECTURE & METHODOLOGY
4. RESULTS AND DISCUSSION
5. CONCLUSION
REFERENCES
참고문헌 (0)
참고문헌 신청함께 읽어보면 좋을 논문
논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!
-
Reconstruction-Based Anomaly Detection with Noise-Induced Normal Sample Augmentation
제어로봇시스템학회 국제학술대회 논문집
2023 .10
-
Using artificial intelligence to detect human errors in nuclear power plants: A case in operation and maintenance
Nuclear Engineering and Technology
2023 .02
-
Unsupervised Learning-Based Anomaly Detection in Industrial Images Using 3D Point Clouds: A Survey
대한전자공학회 학술대회
2024 .06
-
Multiple Encoder based Memory Network for Multivariate Time-series Anomaly Detection
대한산업공학회 추계학술대회 논문집
2022 .11
-
Transformer Encoder에 기반한 비지도 로그 이상 탐지
대한전자공학회 학술대회
2024 .06
-
Autoencoder-based Anomaly Detection
한국통신학회 학술대회논문집
2021 .02
-
Anomaly Detection Algorithm Based on Global Object Map for Video Surveillance System
제어로봇시스템학회 국제학술대회 논문집
2020 .10
-
감시 동영상에서의 시간 모듈을 통한 약한 지도 학습 이상 감지
대한전자공학회 학술대회
2021 .11
-
Anomalous Vessel Behavior Detection Based on SVR Seaway Model
INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS
2019 .03
-
Anomaly Pedestrian Detection using Adversarial Auto-encoder
대한전자공학회 학술대회
2019 .06
-
Pedestrian Anomaly Detection using Adversarial Auto-encoder
대한전자공학회 학술대회
2019 .06
-
Water flow Detection Using Deep Convolutional Encoder-decoder Architecture
제어로봇시스템학회 국제학술대회 논문집
2018 .10
-
Structural health monitoring data anomaly detection by transformer enhanced densely connected neural networks
Smart Structures and Systems, An International Journal
2022 .12
-
딥러닝을 활용한 이상 행동 검출 방법
Proceedings of KIIT Conference
2023 .11
-
패치 회전방향 학습으로 강화된 오토인코더 기반 이상상황 감지 네트워크 구현
대한전자공학회 학술대회
2021 .06
-
설비상태 모니터링을 위한 소리신호 이상치 탐지
한국생산제조학회 학술발표대회 논문집
2022 .12
-
이상치 탐지 기법을 통한 이동 궤적 데이터 분석에 관한 연구
Proceedings of KIIT Conference
2022 .06
-
Normal data based rotating machine anomaly detection using CNN with self-labeling
Smart Structures and Systems, An International Journal
2022 .06
-
[IT-2] Unsupervised Learning Based CNC Machine Anomaly Detection Using Ensemble Techniques
INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING
2024 .01
-
Detecting Anomalous Movement of Human using Clustering Method
한국통신학회 학술대회논문집
2023 .06
이 논문의 저자 정보
최근 본 자료
댓글(0)
0
UCI(KEPA) : I410-ECN-0101-2018-003-003538901