WhatsApp Backup’s Images Segregation
Aditya Bohade, Prarthana Gupta, Om Tulaskar, Suvarna Aranjo
WhatsApp, Deep Learning, Machine Learning, Convolutional Neural Net- work, Python, Keras Library, TensorFlow.
One of the most downloaded apps of all time, WhatsApp allows users to send and receive instant messages from their smartphones. It uses online resources to communicate with individuals or groups using a variety of media types. Its growth has attracted the curiosity of academics who are curious about the impact of WhatsApp on the users' personal and social lives. The proposed model was developed using the Python language's Keras module and the deep learning concept of Convolutional Neural Networks (CNNs). After identifying an image's classification, the corresponding procedure is carried out. CNN has been very successful in the field of image identification. It's a tedious process to go through each WhatsApp folder and manually delete each image that symbolises a study aid, pamphlet, etc. Since then, the research team has developed a machine learning model to locate and retrieve the images from WhatsApp's image folder. Initially, the idea of instructing a computer or gadget to perform a task such as image classification piqued our interest. In addition, the concept can be used in a wide variety of practical contexts. As a result of these considerations, we have settled on the topic of image classification for our research.
Article Details
Unique Paper ID: 159079

Publication Volume & Issue: Volume 9, Issue 11

Page(s): 568 - 579
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