期刊名称：Indian Journal of Computer Science and Engineering
印刷版ISSN：2231-3850
电子版ISSN：0976-5166
出版年度：2021
卷号：12
期号：6
页码：1780-1788
DOI：10.21817/indjcse/2021/v12i6/211206146
语种：English
出版社：Engg Journals Publications
摘要：The internet generates a huge amount of information for a query, but not all of it is useful because it contains some misinformation and some manipulated data. Content-Based Image Retrieval (CBIR) is a state-of-the-art process that is employed by major IT companies all over the world. The research is nearly complete, and they are now being utilized to break the system rather than improving or classifying the right misinformation utilizing state-of-the-art adversarial networks. The major goal of this research is to classify a given misinformation and identify all of the images that were used to create it. A simple general adversarial network (GAN) is utilized in conjunction with an autoencoder to calculate the latent vector. Using the nearest neighbor computation metric, the latent vector is then used to obtain all of the closely matching images. Using the nearest neighbor computation metric, the latent vector is then used to obtain all of the closely matching images. The proposed study has demonstrated that it can retrieve images with much less distance than the current ones and those with a single component than using both in a collaboration. The proposal can lower the same in one-third of the cases already in use.
