PREDICTION AND CLASSIFICATION OF VIDEO FRAMES USING THE KE SIEVE ALGORITHM

Autor:	K. DamodharRao, K. Eswaran
Rok vydání:	2022
Předmět:	Video prediction KE Sieve algorithm sequence of frames next-frame video prediction future events past events
DOI:	10.5281/zenodo.7277491
Popis:	A problem of great interest in the field of computer vision is predicting frames of a video sequence. The success of deep learning in computer vision has led to the emergence of deep-learning-based video prediction as an exciting new study area. The frame prediction is very useful in many applications, such as robot navigation and autonomous vehicles. The focus of our work is to find out the future or past events when a sequence of frames is given. The recent methods used to predict the frames are the convolutional LSTM model and the GAN model.In continuation of the previous paper, in this paper we have used a new machine learning algorithm called the KE Sieve Algorithm to classify and predict the frames in a given set of videos.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6df8d51f3e7ad243b0e21316efa02083 Zobrazit plný text záznamu