https://www.ijert.org/computer-vision https://www.ijert.org/research/computer-vision-IJERTCONV8IS04005.pdf Computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks. a brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation.

the inaugural event in putting together complementary domains were visual approaches are considered in a synergetic view. Visual paradigms were developed on the basis of understanding the brain's and eye's functions. They spread over computation, environment representation, autonomous devices, data presentation, and software/hardware approaches. The advent of Big Data, high speed images/camera, complexity and ubiquity of applications and services raises several requests on integrating visual-based solutions in cross-domain applications. We take here the opportunity to warmly thank all the members of the VISUAL 2017 Technical Program Committee, as well as the numerous reviewers. The creation of such a high quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and efforts to contribute to VISUAL 2017. We truly believe that, thanks to all these efforts, the final conference progra...

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In the dynamic and rapidly evolving landscape of the aviation industry, the effective management of human resources plays a pivotal role in ensuring operational excellence, safety, and customer satisfaction. This study explores the realm of human resource management within the aviation sector, focusing on the strategies that organizations employ to attract, develop, and retain a skilled workforce. Through an in-depth analysis of relevant case studies from various aviation organizations, this research aims to uncover the diverse approaches utilized to address the unique challenges and opportunities of human resource management in this industry. The study explores recruitment and training practices, leadership development, employee engagement initiatives, and the integration of cutting-edge technologies in the aviation context. By synthesizing insights from these cases and existing literature, the research provides valuable insights into the effectiveness of different strategies and their impact on operational performance and organizational success. The findings not only contribute to the academic discourse on human resource management but also offer practical implications for aviation industry professionals and policymakers striving to optimize human capital utilization in the pursuit of excellence.