Tutorial 1
Unobtrusive Sensing with Speech Signals: Techniques, Applications, and Challenges
This tutorial aims to explore how speech signals can be used for unobtrusive sensing in various applications, particularly in health monitoring, emotion recognition, and human-computer interaction. It will cover foundational concepts, practical methods for signal analysis, and current research trends. By the end of the tutorial, participants will understand the role of speech as a passive sensing modality and how it can be leveraged to extract valuable physiological and emotional information.
Organizer
Gauri Deshpande, Tata Consultancy Services Pune, India.
Tutorial 2
Artificial Intelligence Models for Land Use Land Cover Mapping from Satellite Remote Sensing Images
Land cover mapping using remote-sensing imagery has attracted significant attention in recent years. Classification of land use and land cover is an advantage of remote sensing technology which provides all information about land surface. Numerous studies have investigated land cover classification using different broad array of sensors, resolution, feature selection, classifiers, classification Techniques, and other features of interest over the past decade. Pixel-based and Image-based classification techniques are used for land use land cover classification from satellite remote sensing images. Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, and management of the Earth. With the advent of cloud computing platforms and machine learning deep learning classifiers, new opportunities are arising in more accurate and large-scale LULC mapping from satellite remote sensing images. Deep learning-based segmentation of high-resolution satellite images is a significant task providing valuable information for various geospatial applications, specifically for land use/land cover (LULC) mapping from remote sensing images. The segmentation task becomes more challenging with the increasing number and complexity of LULC classes. This tutorial session presents a detailed introduction and implementation of Artificial Intelligence Models for land use/land cover (LULC) mapping from Satellite Remote sensing images. Finally, Practical Implementation and demonstration of 2D UNet and Attention UNet CNN models for land use/land cover (LULC) mapping from Satellite Images using Python Programming and Deep Learning TensorFlow Library.
Organizers
Shyam Lal, National Institute of Technology Karnataka, India
Mahendra Pratap Singh, National Institute of Technology Karnataka, India.
Tutorial 3
IoT Design with ESP32: A Hands-on Tutorial
This ESP32 tutorial course provides a hands-on guide to mastering wireless communication using the versatile ESP32 microcontroller. The course introduces various tools and demonstrates how they can aid in IoT project development. Learners will create, configure, and simulate different IoT projects. Additionally, we will explore how to integrate and configure various sensors and actuators, and write code to interact with them. By the end of the course, learners will be able to build and deploy IoT applications that fully leverage the wireless capabilities of the ESP32 for real-world projects.
Organizer
Praveen Pawar, Visvesvaraya National Institute of Technology, Nagpur, India.
Tutorial 4
Decoding human thoughts through EEG signal processing
Decoding human thoughts is a powerful technique that can assist paralyzed people who have lost their speech production ability. Speaking is a combined process involving synchronizing the brain and the oral articulators. Among various brain signals monitoring technologies, EEG has been proven to be one of the most popular methods for monitoring brain activities due to its cost-effectiveness and non-invasiveness. This tutorial presents the concept of decoding human thoughts via EEG signal processing. Tutorial will cover brain signal acquisition using EMOTIV tool, data analysis through EMOTIV analyser and decoding inner speech using machine learning methods.
Organizers
Pradnya Ghare, Visvesvaraya National Institute of Technology, Nagpur, India.