Displaying 273 resources
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
An Introduction to PAC-Bayesian Analysis
This resource corresponds to 9th video from the AI Excellence Lecture Series.
PAC-Bayesian Analysis is a framework in machine learning and statistics that combines ideas from the Probably Approximately Correct (PAC) learning framework and Bayesian p
Video Captioning
This lecture overviews Video Captioning that has many applications in video description, search and retrieval. It covers the following topics in detail: Video captioning definitions and datasets.
Autonomous Systems Sensors
This lecture overviews Autonomous Systems Sensors that has many applications in Autonomous robots, cars, vessels and drones.
A survey of manifold learning and its applications for multimedia, Hannes Fassold, Proc. ICVSP, 2023
The survey paper gives an introduction into manifold learning and how it is employed for important application fields (similarity search, image classification, synthesis & enhancement, video analysis, 3D data processing, nonlinear dimension reduc
Pedestrian Detection
This lecture overviews Pedestrian Detection that has many applications in autonomous car vision and smart city applications.
Deep Semantic Image Segmentation
Semantic image segmentation is a very important computer vision task with several applications in autonomous systems perception, robotic vision and medical imaging.
Road Traffic Monitoring
This lecture overviews Road Traffic Monitoring that has many applications in in autonomous car perception and smart city management.
3D Object Localization
This lecture overviews 3D Object Localization that has many applications in robotics and autonomous systems.
Active and Passive 3D shape reconstruction methods
This lecture overviews Active and Passive 3D shape reconstruction methods that has many applications in 3D computer vision, autonomous systems perception and medical imaging.
Kernel methods
This lecture overviews Kernel Methods that have many applications in classification and clustering. It covers the following topics in detail: Kernel Trick. Kernel Matrix. Kernel PCA. Kernel correlation and its use in object tracking. Kernel k-means.
Domain Adaptation
This lecture overviews Domain Adaptation that has many applications in DNN training and adaptation.