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INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
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| Paper Title: | Human behavior and abnormality detection using Yolo and CONV2D |
| Authors Name: | Vattikunta Mahitha , ALLENKI USHA REDDY , Jangili Sunitha , Dr.P.Rama |
| Unique Id: | IJSDR2304168 |
| Published In: | Volume 8 Issue 4, April-2023 |
| Abstract: | As it can be used in surveillance, security, and healthcare, the detection of anomalous human behavior is a crucial topic of research in computer vision. Deep learning methods like YOLO (You Only Look Once) and CONV2D (Convolutional Neural Network 2D) have recently found success in the detection of anomalous human behavior. The cutting-edge object detection technology YOLO can accurately identify and classify things in real-time. By breaking a picture into a grid of cells, YOLO's deep neural network predicts bounding boxes and class probabilities for each cell. By training the model on a dataset of labeled films of both normal and pathological human behavior, YOLO has been used to detect human behavior. The model is then capable of real-time detection of anomalous behavior like fighting, falling, or loitering. A typical neural network layer used in image processing and computer vision tasks is CONV2D. The input image is subjected to a convolution operation using CONV2D, which aids in the extraction of features like edges and textures. After that, these traits are employed to categorize or identify things in the image. By training the model using a collection of labeled photos or videos of normal and abnormal behavior, CONV2D has been used to detect abnormal human behavior. The model can then discover patterns or traits that are different from typical behavior in order to detect aberrant activity. In conclusion, the powerful deep learning methods YOLO and CONV2D can be utilized to identify anomalous human behavior. These methods can be used to increase people's safety and wellbeing in society and have applications in a number of areas, including surveillance, security, and healthcare. |
| Keywords: | Abnormality detection , Yolo v5 |
| Cite Article: | "Human behavior and abnormality detection using Yolo and CONV2D", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 4, page no.1009 - 1016, April-2023, Available :http://www.ijsdr.org/papers/IJSDR2304168.pdf |
| Downloads: | 000337074 |
| Publication Details: | Published Paper ID: IJSDR2304168 Registration ID:205254 Published In: Volume 8 Issue 4, April-2023 DOI (Digital Object Identifier): Page No: 1009 - 1016 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
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