This Summer School presents recent deep learning and computer vision advances as applied in Natural Disaster Management (Horizon Europe TEMA project).
Part A will focus on Deep Learning and GPU programming. The lectures of this part provide a solid background on Deep Neural Networks (DNN) topics, notably convolutional NNs (CNNs) and deep learning for image classification. Also, Knowledge Distillation methods in DNNs will be presented. Two programming workshops will take place. The first one will be on image classification using CNNs, while the second one will be on knowledge distillation for different DNN architectures to achieve faster inference times in embedded systems.
Part B lectures will focus on deep learning algorithms for Perception on Autonomous Systems, namely on 2D object/face detection and 2D object tracking. The hands-on programming workshop will be on target detection with PyTorch and on how to use OpenCV (the most used library for computer vision) for target tracking.
Part C lectures will focus on Autonomous Systems in Natural Disaster Management (NDM). The lectures will provide a basic understanding of Real-Time Image Segmentation algorithms. The partitioners will be able to use DNNs in a hands-on programming workshop for Image Segmentation on Natural Disaster Optical Flow data (e.g., videos of floods). Moreover, methods for using Natural Language Processing in NDM will be presented. A programming workshop on exploiting text data from social media (e.g., twitter) with DNNs will take place.
The lectures and programming tools will provide programming skills for the various computer vision and deep learning problems encountered in Autonomous Systems for Natural Disaster Management, e.g., neural knowledge distillation, real-time object detection, tracking, image segmentation, NLP etc.
Lectures and programming workshops will be in English. PDF files will be available at the end of the course.
Part A (8 hours) Deep Learning for Autonomous Systems
Deep neural networks – Convolutional NNs.
Knowledge Distillation in Deep Neural Networks.
Programming workshop on Deep neural networks – Convolutional NNs.
Programming workshop on Knowledge Distillation in Deep Neural Networks.
Part B (8 hours) Autonomous Systems Perception
Real Time Object Detection.
2D Object Tracking in Embedded Systems.
Programming workshop on Real Time Object Detection.
Programming workshop on 2D Object Tracking in Embedded Systems.
Part C (8 hours) Autnomous Systems in Natural Disaster Management
Real-Time Image Segmentation.
Natural Language Processing for Natural Disaster Management.
Programming workshop on Real-Time Image Segmentation.
Programming workshop on Natural Language Processing for Natural Disaster Management.
