Litcius/Paper detail

Bare Skin Image Classification using Convolution Neural Network

Jaya Gupta, Sunil Pathak, Gireesh Kumar

2022International Journal of Emerging Technology and Advanced Engineering13 citationsDOIOpen Access PDF

Abstract

Image classification is critical and significant research problems in computer vision applications such as facial expression classification, satellite image classification, and plant classification based on images. Here in the paper, the image classification model is applied for identifying the display of daunting pictures on the internet. The proposed model uses Convolution neural network to identify these images and filter them through different blocks of the network, so that it can be classified accurately. The model will work as an extension to the web browser and will work on all websites when activated. The extension will be blurring the images and deactivating the links on web pages. This means that it will scan the entire web page and find all the daunting images present on that page. Then we will blur those images before they are loaded and the children could see them. Keywords— Activation Function, CNN, Images Classification , Optimizers, VGG-19

Topics & Concepts

Computer scienceConvolutional neural networkArtificial intelligenceImage (mathematics)The InternetContextual image classificationConvolution (computer science)Filter (signal processing)Pattern recognition (psychology)Web pageArtificial neural networkExtension (predicate logic)Computer visionFunction (biology)World Wide WebBiologyEvolutionary biologyProgramming languageCOVID-19 diagnosis using AICurrency Recognition and DetectionFace and Expression Recognition