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Article/Books/eBooks
Learning to Quantify
This book provides an introduction and an overview of learning to quantify (a.k.a. “quantification”), the task of training, by means of supervised learning, estimators of class proportions in unlabelled data.
Introduction to Computer Vision
A detailed introduction to computer vision will be made: image/video sampling, Image and video acquisition, Camera geometry, Stereo and Multiview imaging, Structure from motion, Structure from X, 3D Robot Localization and Mapping, Semantic 3D world m
e-Symposium 2023: A methodology for Forecasting Election results from Tweets
Social networks as the virtual equivalent of the ancient agora have become a preeminent space of political discourse. They can nurture new political trends and reveal existing ones.
Representation Learning for Natural Language Processing
Provides a comprehensive overview of the representation learning techniques for natural language processing.
Presents a systematic and thorough introduction to the theory, algorithms and applications of representation learning.
Shares insights into
Video Description
This lecture overviews that has many applications in broadcasting archives abd video description, search, retrieval and browsing.
ECG Signal Analysis
This lecture overviews ECG Signal Analysis as well as other cardiology imaging methods that has many applications in cardiological disorder diagnosis and treatment. It covers the following topics in detail: Background nnowledge of ECG Signals.
Fast 1D Convolution Algorithms
1D convolutions are extensively used in digital signal processing (filtering/denoising) and analysis (also through CNNs). As their computational complexity is of the order O(N^2), their fast execution is a must.
This lecture will overview
Federated Learning
This lecture overviews that has many applications in distributed Machine Learning and privacy protection.
Soccer Video Analysis
This lecture overviews Soccer Video Analysis that has many applications in Human-centered Computing, Image and Video Analysis and Sports Analytics/coaching.
Dimensionality Reduction
This lecture overviews Dimensionality Reduction that has many applications in object clusring and object recognition. It covers the following topics in detail: Feature selection. Principal Component Analysis. Linear Discriminant Analysis.
From Images to Text New forms of Human-AI Interaction
Recent progress in the Computer Vision and Natural Language Processing communities have made it possible to connect Vision and Language together in a variety of different tasks which lie at the intersection of Vision, Language, and Embodied AI.
Multilayer perceptron. Backpropagation
This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.