A Systematic Literature Review on Image Captioning

Natural language problems have already been investigated for around five years. Recent progress in artificial intelligence (AI) has greatly improved the performance of models. However, the results are still not sufficiently satisfying. Machines cannot imitate human brains and the way they communicate, so it remains an ongoing task. Due to the increasing amount of information on this topic, it is very difficult to keep on track with the newest researches and results achieved in the image captioning field. In this study a comprehensive Systematic Literature Review (SLR) provides a brief overview of improvements in image captioning over the last four years. The main focus of the paper is to explain the most common techniques and the biggest challenges in image captioning and to summarize the results from the newest papers. Inconsistent comparison of results achieved in image captioning was noticed during this study and hence the awareness of incomplete data collection is raised in this paper. Therefore, it is very important to compare results of a newly created model produced with the newest information and not only with the state of the art methods. This SLR is a source of such information for researchers in order for them to be precisely correct on result comparison before publishing new achievements in the image caption generation field.This article belongs to the Section Computing and Artificial Intelligenc

Reconocimiento de acciones deportivas en secuencias de vídeo mediante técnicas de aprendizaje automático

Se va a tratar de desarrollar una herramienta que sea capaz de reconocer acciones de tenis en secuencias de vídeo mediante técnicas de machine learning. Se va a crear una base de datos adecuada a las ontologías relativas a la actividad elegida (tenis), a partir de ella, se van a estudiar diferentes metodologías de tratamiento de imágenes con el fin de extraer características para, posteriormente, analizarlas mediante técnicas de machine learning. La validez de los resultados obtenidos junto al estado del arte nos permitirá llegar a unas conclusiones y nos descubrirá nuevos enfoques sobre el reconocimiento de acciones y personas.<br /