TensorFlow Implementation on Analysis of Unusual Behavior in Crowd Using Deep Learning
TensorFlow Implementation on Analysis of Unusual Behavior in Crowd Using Deep Learning
- New search for: P, Manoj Kumar D
- New search for: Babu J, Ananda
- New search for: S, Varsha T
- New search for: N, Spoorthy
- New search for: B, Rekha
- New search for: Sharma, Sanyam
- New search for: P, Manoj Kumar D
- New search for: Babu J, Ananda
- New search for: S, Varsha T
- New search for: N, Spoorthy
- New search for: B, Rekha
- New search for: Sharma, Sanyam
Image processing and computer vision researchers can effectively use real-time video to identify human behavior. With the use of visuals, it is possible to observe human activity in private and public places including car parks, bus stops, train stations, airports, banks, retail centers, schools, and colleges. It was done to stop crimes, terrorism, theft, fights, chain exploitation, accidents, unauthorized parking, graffiti, and other shady activities. Since it is highly challenging to constantly observe public spaces, there is a need for intelligent video surveillance that can track people's movements in real-time, differentiate between typical and odd activity, and possibly even sound an alarm.
Document information
TensorFlow Implementation on Analysis of Unusual Behavior in Crowd Using Deep Learning
2023-11-23
1403569 byte
Conference paper
Electronic Resource
English
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