Publication | Closed Access
Fake Image Detection in Twitter using Flood Fill Algorithm and Deep Neural Networks
34
Citations
17
References
2022
Year
Background:One of the primary concerns in online social networks is fake image or fake colorized image diffusion, which allows anyone to add, remove, and alter the images.Purpose:Till now it is not possible to develop a model or a technique that can accurately recognize or categorize images as fake or genuine.Method:In this paper we are trying to utilize the flood fill algorithm to In this paper we are trying to utilize the flood fill algorithm to highlight the forged object in the image and a Deep Learning based solution is proposed to detect whether the image is fake or genuine. We collect twitter dataset, which is given as input to the deep learning models and train them to identify whether the image is fake or genuine.Result:Experimental evaluations showed that the proposed framework can detect the fake images that have been diffused in Twitter with 96% accuracy.
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