ADR Awareness Centre

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

Deep Convolutional Generative Adversarial Networks (DCGAN) have been used to generate highly compelling pictures or videos, such as manipulated facial animations, interior and outdoor images, videos.

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

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

This lecture overviews Neural Image Compression that has many applications in image storage and communications.

This lecture overviews various concepts related to multiple drone communications: LTE and WiFi communications, LTE communication infrastructure, IP network issues, Security analysis, throughput, latency and quality-of-service issues.

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.

Semantic image segmentation is a very important computer vision task with several applications in autonomous systems perception, robotic vision and medical imaging.

This lecture overviews discrete-time Signals and Systems topics. Discrete-time signals are presented: periodic signals, delta signal, unit step signal, exponential signal, trigonometric signals, complex exponential signal.

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.

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

This lecture overviews Neural SLAM   that has many applications in robotic and autonomous vehicle localization and mapping.