This thesis project presents a novel approach for detecting corrosion using drone-based surveillance systems by modifying the YOLOv5 object detection model and deploying it to a VOXL 2 flight controller for real-time image processing. The central goal is to enhance the model's accuracy in detecting corrosion …

Google wants to “help computers ‘see’ our world”, and one of their ways of battling how current AI and machine learning systems perpetuate biases is to introduce a more inclusive scale of skin tone, the ‘Monk Skin Tone Scale’.

In this work, a feasible and low-cost approach is proposed for level measurement in multiphase systems inside tanks used for petroleum-derived oil production. The developed level sensor system consisted of light-emitting diodes (LEDs), light-dependent resistor (LDR), and a low-cost microprocessor. Two …

Machine learning models have been an inevitable tool for analyzing medical images by radiologists. These models provide important information about the contents of these images using extracted radiomic features. However, the dimensionality of the feature space can cause reduction in the accuracy of prediction, …

The prevention and diagnosis of frailty syndrome (FS) in cardiac patients requires innovative systems to support medical personnel, patient adherence, and self-care behavior. To do so, modern medicine uses a supervised machine learning approach (ML) to study the psychosocial domains of frailty in cardiac …

Validation of AI: Towards a Driving Exam for OpenPilotWe present practical results of testing the OpenPilot ADAS software (the core of the Comma3 [https://comma.ai/]). OpenPilot consists of C/C++ and Python code to handle most of the logic involved in driving a car. Also, Machine Learning models are …

The recent advancements in machine learning (ML) techniques have significantly improved the performance in various natural language processing (NLP) tasks, particularly in deep learning with the transformer architecture. Despite their promising applications in different domains, these innovations have …

The use of machine learning in embedded systems is an interesting topic, especially with the growth in popularity of the Internet of Things (IoT). The capacity of a system, such as a robot, to self-localize, is a fundamental skill for its navigation and decision-making processes. This work focuses on …

Nowadays, one of the major current health risks is excessive sitting during work hours. Furthermore, the coronavirus disease 2019 (COVID-19) pandemic and the corresponding government state of emergency forced many people to work from home. These constraints carried out an important change in the lifestyle …

This documentation covers a feasability study on Computer Vision to register Data Matrix Codes using Machine learning. The documentation covers the topics of selecting the components of the system, the type of training data needed to train an Object Detection Model using Machine Learning, and the processes …