With the advent of technology and communication media, it is now possible to gather and integrate data via a digital medium. Data sharing without authorization via electronic media is referred to as a breach of digital privacy. The right to privacy is a human right that is guaranteed by law in nearly every country and has been extended to those who are under trial/ accused. At the same time, the press, including digital media, has the right to freedom of expression. This paper examines the unwarranted intervention of digital media in the personal lives of both the victim and the accused. Inquisitorial as well as adversarial models of judicial process presume the accused innocent until guilt is proven after following the due process of law. This paper investigate the unrestrained and irresponsible publication of news and posts that violate a person's data privacy and available remedies in the law when rights to privacy are breached. It also comparatively examine privacy laws and legal remedies in the United States, the United Kingdom, and India, and make appropriate recommendations. Study of this paper reveals that in the wake of rising interferences by media, there is no specific statute providing protections.

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Taking into account the uses of ML in the field of vision, many practical vision systems' first processing stages include enhancing or reconstructing images. The goal of these tools is to enhance the quality of photos and give accurate data for making decisions based on appearance. In this research study, the authors examine three distinct types of neural networks: convolutional networks, residual networks, and generative countermeasure networks. There is a proposal for a model structure of a scalable supplementary generation network as part of a network that enhances evidence images as a generative countermeasure. The authors present the objective loss function definition, as well as the periodic consistency loss and the periodic perceptual consistency loss analysis. An in-depth solution framework for picture layering is offered once the problem's core aspects are explained. This approach implements multitasking with the help of adaptive feature learning, this provides a strong theoretical guarantee.