Identifying suspicious human activity using artificial intelligence and deep recognition
Session
Mechatronics, System Engineering and Robotics
Description
Every day we are on the move, we are active during the process of going to work, to studies and for all our daily activities that complete our day. We as human beings always tend to be different from each other, this difference manifests itself with its positive and negative sides. The negative actions of many people have a legal categorization in terms of punishment, but history has taught us that there are moments and cases when malicious actions are of such a level that the punishment that can be given to a person for that action is not proportionate with the damage caused. To prevent malicious actions, it has always been invested in technological assets and people who, by monitoring them, could contribute to society to prevent suspicious actions that could bring irreparable consequences and high human losses. Human interest reputation is a critical but difficult topic to study and predict through technological devices. In this paper, we will present the techniques, practices and algorithms used to identify suspicious human activities using artificial intelligence and deep recognition.
Keywords:
Activity recognition; Deep learning; Human activities; Artificial intelligence.
Proceedings Editor
Edmond Hajrizi
ISBN
978-9951-550-50-5
Location
Lipjan, Kosovo
Start Date
29-10-2022 12:00 AM
End Date
30-10-2022 12:00 AM
DOI
10.33107/ubt-ic.2022.84
Recommended Citation
Morina, Vesa and Sejdiu, Shqipe, "Identifying suspicious human activity using artificial intelligence and deep recognition" (2022). UBT International Conference. 84.
https://knowledgecenter.ubt-uni.net/conference/2022/all-events/84
Identifying suspicious human activity using artificial intelligence and deep recognition
Lipjan, Kosovo
Every day we are on the move, we are active during the process of going to work, to studies and for all our daily activities that complete our day. We as human beings always tend to be different from each other, this difference manifests itself with its positive and negative sides. The negative actions of many people have a legal categorization in terms of punishment, but history has taught us that there are moments and cases when malicious actions are of such a level that the punishment that can be given to a person for that action is not proportionate with the damage caused. To prevent malicious actions, it has always been invested in technological assets and people who, by monitoring them, could contribute to society to prevent suspicious actions that could bring irreparable consequences and high human losses. Human interest reputation is a critical but difficult topic to study and predict through technological devices. In this paper, we will present the techniques, practices and algorithms used to identify suspicious human activities using artificial intelligence and deep recognition.