Advancements in NSFW Content Detection: A Comprehensive Review of ResNet-50 Based Approaches
Keywords:
ML: Machine Learning, CNN: Convolutional Neural Network, ResNet, Residual Network, SFW: Safe for Work, NSFW: Not Safe for WorkAbstract
The exponential growth of explicit images posted on social media is increasing day-by- day. With children and minors having unrestricted access to the internet, the rapidly rising availability of pornographic content has created many difficulties in modern life. Therefore, there is a need to build a system that will detect the explicit content in an image and the text present in the image. In this system a deep learning-based architecture is used to detect the images and text in images. The proposed system employs a pre-trained convolutional neural network (CNN) model known as ResNet50 to classify the image as safe or not safe. The existing system used only CNN in image detection, and it resulted in less accuracy, whereas our proposed system uses ResNet50 and is expected to give more accuracy as compared to the existing system.
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