[ad_1] Introduction Stereo matching is a significant area of research in computer vision and image processing, which aims to estimate the disparity map between a pair of stereo images. Disparity estimation plays a crucial role…
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[ad_1] Introduction Instance segmentation is a computer vision task that aims to detect individual object instances in an image and classify each pixel as belonging to a particular object category. This process is crucial for…
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[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…
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[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…
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[ad_1] Introduction: Gesture recognition is a technology that allows a computer to interpret human gestures as commands for controlling devices or interacting with software applications. It has gained popularity as a natural and intuitive way…
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[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…
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[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…
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[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…
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[ad_1] Introduction Recurrent neural networks (RNNs) have gained significant attention in recent years for their ability to model sequential data and make predictions based on this data. In particular, recurrent neural network language models have…
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[ad_1] Introduction: Restricted Boltzmann Machines (RBMs) have gained popularity in recent years as a powerful tool for unsupervised feature learning in machine learning. RBMs are a type of artificial neural network that can learn a…
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