HYBRIDIZED R-CNN ResNet-50FPN WITH MULTILAYER PERCEPTRON INTEGRATED WITH NLP TO DETECT FAULTS IN CCTV SMPS

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G.V.S.Manoj Kumar 1, M. Anand 2 & K.S.Thivya 3

Vol 18, No 5 ( 2023 )   |  Licensing: CC 4.0   |   Pg no: 58-70   |   Published on: 10-05-2023

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Abstract
An efficient fault detection model is designed for CCTV SMPS integrated along with an effective self-learning natural language-based chatbot. For creating a computer vision model Torchvision was employed. Faster R-CNN ResNet-50FPN & fully connected neural network, also known as a multilayer perceptron (MLP) is hybridized and serves as an optimized detection model. Fault detection is carried out using the proposed model. PyCharm Community, Python, and Streamlit is used to create a streamlined self-learning natural language-based chatbot . The self-learning natural language-based chatbot has been designed to operate smoothly and learn quickly, with a focus on delivering accurate and helpful responses to users.

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