A Novice Approach of Hybrid Transfer Learning for Video Classification

Abstract

One of the very interesting data modalities is video. From a dimensionality and size perspective, videos are one of the most interesting and intuitive data types which enable fast and easy object recognition and learning. Video classification is an important task for archiving digital contents for various video service providers. Video uploading platforms such as YouTube are collecting enormous datasets, empowering Deep Learning research. Video being an important source to recognize any activity by the humans, video classification becomes an important and critical job for video service providers. The survey paper studies various deep learning, transfer learning and hybrid model approaches.