Online ISSN: 2515-8260

Keywords : AI


Investigation and development of machine Learning Challenges in Video Interviews

DILIP KUMAR SHARMA; ASHISH SHARMA

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 425-433

This paper audits and talks about examination propels on "logical AI" in PC vision. We centre on a specific zone of the "Seeing People" (LAP) topical space: primary imitations and character investigation. Our point is to variety the computational knowledge and PC vision networks mindful of the significance of creating logical systems for PC helped dynamic applications, for example, robotizing enlistment. Decisions dependent on character attributes are being made routinely by human asset offices to assess the up-and-comers' ability of social inclusion and their capability of profession development. Be that as it may, deducing character attributes and, as a rule, the procedure by which we people structure a first impression of individuals, is profoundly emotional and might be one-sided. Past investigations have shown that knowledge machineries can figure out how to imitate human choices. In this paper, we go above and beyond and figure the issue of clarifying the choices of the models as methods for distinguishing what visual perspectives are significant, seeing how they identify with choices recommended, and potentially picking up knowledge into unfortunate negative inclinations. We structure another test on reasonableness of knowledge machineries for first impressions examination. We portray the setting, situation, assessment measurements and starter results of the opposition. Supposedly this is the first exertion regarding difficulties for logic in PC vision. Moreover, our test configuration involves a few other measurable and subjective components of oddity, including a "competition" setting, which joins rivalry and coordinated effort.

Deep Learning in Tuberculosis Diagnosis: A Survey

B. Sandhiya; Dr.R. Punniyamoorthy; Saravanan. B; Vijay Prabhu. R; Subhash. V

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 4, Pages 2736-2740

Tuberculosis is a contagious syndrome that leads to death Worldwide. In majority of the developing countries, the access to the diagnostic tool and the test usage is relatively poor. Now the recent advancement in the field of Artificial Intelligence may help them to fill this technology gap. Computer Aided Detection and Diagnosis helps in diagnosing the diseases through some clinical symptoms as well as X-ray images of the patients. Nowadays many strategies are formulated to increase the classification accuracy of tuberculosis diagnosis using AI and Deep Learning approaches. Our survey paper, focus to describe the wide AI and deep learning approaches employed in the diagnosis of tuberculosis.