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Action recognition for video understanding – Complete Phd and Masters Thesis

[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…

Image captioning for visual description generation – Complete Phd and Masters Thesis

[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…

Recurrent neural network language models for sequence prediction – Complete Phd and Masters Thesis

[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…

Convolutional deep belief networks for spatial data – Complete Phd and Masters Thesis

[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…

Deep belief networks for hierarchical representation – Complete Phd and Masters Thesis

[ad_1] Introduction In recent years, deep belief networks (DBNs) have gained significant attention in the field of artificial intelligence and machine learning due to their ability to learn hierarchical representations of data. These networks are…

Self-organizing maps for topology preservation – Complete Phd and Masters Thesis

[ad_1] Introduction Self-organizing maps (SOMs) have been widely used in various fields such as machine learning, data visualization, pattern recognition, and clustering. One of the key advantages of SOMs is their ability to preserve the…

Autoencoders for unsupervised representation learning – Complete Phd and Masters Thesis

[ad_1] Introduction Autoencoders have gained significant attention in recent years as powerful tools for unsupervised representation learning. These neural networks are capable of learning compact and meaningful representations of data without the need for labeled…

Convolutional neural networks for spatial data – Complete Phd and Masters Thesis

[ad_1] Introduction Convolutional neural networks (CNNs) have gained significant attention in recent years due to their exceptional performance in various domains, including computer vision, natural language processing, and speech recognition. CNNs are particularly well-suited for…

Artificial neural networks for universal approximation – Complete Phd and Masters Thesis

[ad_1] Introduction Artificial Neural Networks (ANNs) have become a popular tool in the field of machine learning and artificial intelligence due to their ability to approximate complex functions. In recent years, ANNs have been used…

Random forests for ensemble learning – Complete Phd and Masters Thesis

[ad_1] Introduction Random forests are a powerful ensemble learning method that has gained popularity in various fields of study, including machine learning, data mining, and bioinformatics. This thesis focuses on understanding the principles behind random…

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