[ad_1] Thesis Overview: Title: Optical flow estimation for motion analysis Introduction: In the field of computer vision, optical flow estimation is a critical task that involves tracking the movement of objects in a sequence of…
Read More
[ad_1] Introduction Semantic segmentation is a crucial task in computer vision that involves assigning a class label to each pixel in an image. This technique plays a significant role in various applications such as autonomous…
Read More
[ad_1] Introduction Scene understanding refers to the ability of a computer system to interpret and make sense of visual data in a given environment. This process involves recognizing objects, inferring relationships between them, and understanding…
Read More
[ad_1] Introduction Action recognition is a crucial task in video understanding and has gained significant attention in recent years due to its wide range of applications in various fields such as surveillance, human-computer interaction, sports…
Read More
[ad_1] Introduction: Gaze estimation for attention tracking has become a prominent research area in recent years, with applications in various fields such as human-computer interaction, psychology, and medical diagnosis. The ability to accurately estimate where…
Read More
[ad_1] Introduction In recent years, the explosion of online video content has created a need for automated methods of video summarization for highlight extraction. Video summarization involves condensing the content of a video into a…
Read More
[ad_1] Introduction: Visual question answering (VQA) is an emerging research area that aims to enable machines to understand and answer questions about visual content. With the increasing availability of multimedia data, including images and videos,…
Read More
[ad_1] Introduction 1.1 Introduction 1.2 Background of study 1.3 Problem Statement 1.4 Objective of study 1.5 Limitation of study 1.6 Scope of study 1.7 Significance of study 1.8 Structure of the Thesis 1.9 Definition of…
Read More
[ad_1] Introduction Neural machine translation has revolutionized the field of automated translation in recent years. Traditional machine translation systems relied on complex rule-based approaches that struggled with the nuances of language. However, neural machine translation,…
Read More
[ad_1] Introduction In recent years, there has been a growing interest in the development and application of deep learning techniques for the analysis of spatial data. Convolutional Deep Belief Networks (CDBNs) have emerged as a…
Read More