A Review of Image Enhancement Techniques for Underwater Images
Abstract
This paper presents a review of aquatic image improvement ways which serves as the foundation of a variety of aquatic imaging operations including the study of submarine life forms, aquatic object discovery and bracket or simply an enhancement in the appearance of aquatic images. Unlike regular imaging in a normal terrain, aquatic imaging suffers from reduced clarity, included by scattering and immersion of light. There are regions withnon-uniform illumination and prominent bluish and greenish tones depending on the wavelength of light. The quality of aquatic images also depends on the photographic device used to capture the image, turbidity of water. This paper discusses the different types of improvement brought about by varied aquatic image improvement ways.
A SMART SYSTEM FOR FAKE NEWS DETECTION USING MACHINE LEARNING
Abstract
Most of the smart phone users prefer to read the news via social media over internet. The news websites are publishing the news and provide the source of authentication. The question is how to authenticate the news and articles which are circulated among social media like WhatsApp groups, Facebook Pages, Twitter and other micro blogs & social networking sites. It is harmful for the society to believe on the rumors and pretend to be a news. The need of an hour is to stop the rumors especially in the developing countries like India, and focus on the correct, authenticated news articles. This paper demonstrates a model and the methodology for fake news detection. With the help of Machine learning and natural language processing, it is tried to aggregate the news and later determine whether the news is real or fake using Support Vector Machine. The results of the proposed model is compared with existing models. The proposed model is working well and defining the correctness of results upto 93.6% of accuracy.