Abnormal Activity Detection Using Deep Learning

2022 ◽  
pp. 675-682
Author(s):  
A. Dhanush Kumar ◽  
P. Shushruth Reddy ◽  
Kriti C. Parikh ◽  
C. Meghana Sarvani ◽  
P. Loel Maansi
Keyword(s):  
Deep Learning ◽  
Activity Detection ◽  
Abnormal Activity Detection

Deep Learning Techniques for Koala Activity Detection

2018 ◽  
Author(s):  
Ivan Himawan ◽  
Michael Towsey ◽  
Bradley Law ◽  
Paul Roe
Keyword(s):  
Deep Learning ◽  
Activity Detection ◽  
Learning Techniques

Suspicious activity detection using deep learning in secure assisted living IoT environments

2020 ◽  
Author(s):  
G. Vallathan ◽  
A. John ◽  
Chandrasegar Thirumalai ◽  
SenthilKumar Mohan ◽  
Gautam Srivastava ◽  
...  
Keyword(s):  
Deep Learning ◽  
Assisted Living ◽  
Activity Detection ◽  
Suspicious Activity

Human Activity Detection Using Deep Learning and Bracelet with Bluetooth Transmitter

2021 ◽  
Author(s):  
Stevan Cakic ◽  
Stevan Sandi ◽  
Daliborka Nedic ◽  
Srdan Krco ◽  
Tomo Popovic
Keyword(s):  
Deep Learning ◽  
Human Activity ◽  
Activity Detection ◽  
Human Activity Detection

Deep learning approaches for video-based anomalous activity detection

2018 ◽  
Vol 22 (2) ◽  
pp. 571-601 ◽  
Author(s):  
Karishma Pawar ◽  
Vahida Attar
Keyword(s):  
Deep Learning ◽  
Learning Approaches ◽  
Activity Detection

scholarly journals Comparing Video Activity Classifiers within a Novel Framework

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1545
Author(s):  
Chiman Kwan ◽  
Bence Budavari ◽  
Bulent Ayhan
Keyword(s):  
Deep Learning ◽  
Image Retrieval ◽  
General Framework ◽  
Experimental Results ◽  
Analysis Tool ◽  
Activity Detection ◽  
Rule Based ◽  
Event Classification ◽  
Hybrid Combination ◽  
Rule Based Approach

Video activity classification has many applications. It is challenging because of the diverse characteristics of different events. In this paper, we examined different approaches to event classification within a general framework for video activity detection and classification. In our experiments, we focused on event classification in which we explored a deep learning-based approach, a rule-based approach, and a hybrid combination of the previous two approaches. Experimental results using the well-known Video Image Retrieval and Analysis Tool (VIRAT) database showed that the proposed classification approaches within the framework are promising and more research is needed in this area

Pecking activity detection in group-housed turkeys using acoustic data and a deep learning technique

2020 ◽  
Vol 194 ◽  
pp. 40-48 ◽  
Author(s):  
Abozar Nasirahmadi ◽  
Jennifer Gonzalez ◽  
Barbara Sturm ◽  
Oliver Hensel ◽  
Ute Knierim
Keyword(s):  
Deep Learning ◽  
Activity Detection ◽  
Acoustic Data ◽  
Learning Technique
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