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Autonomous Driving: Integration of Segmentation and Depth Camera in a Curriculum Learning Approach

Autonomous driving (AD) entails vehicles that can perceive their surroundings and navigate without human intervention. This involves utilising a combination of sensors and algorithms to recognize obstacles, interpret traffic signals, and make driving …

Automated Classification of Test Tubes Based on Uncontrolled Image Analysis

Metrology, the science of measurement, involves defining and establishing standards for quantifying physical quantities. A critical aspect of this discipline is to accurately measure and understand the relationships between object dimensions. …

Investigating the Effectiveness of 3D Monocular Object Detection Methods for Roadside Scenarios

Urban environments are demanding effective and efficient detection in 3D of objects using monocular cameras, e.g., for intelligent monitoring or decision support. The limited availability of large-scale roadside camera datasets and the mere focus of …

Multi-scale deep learning ensemble for segmentation of endometriotic lesions

Ultrasound is a readily available, non-invasive and low-cost screening for the identification of endometriosis lesions, but its diagnostic specificity strongly depends on the experience of the operator. For this reason, computer-aided diagnosis tools …

FootApp:an AI-powered system for football match annotation

In the last years, scientific and industrial research has experienced a growing interest in acquiring large annotated data sets to train artificial intelligence algorithms for tackling problems in different domains. In this context, we have observed …

A Facial Expression Recognition Approach for Social IoT Frameworks

Social IoT has become a sensitive topic in the last years, mainly due to the attraction of social networks and the related digital activities amongst the population. These techniques are gaining even more importance in the current period, in which …

An End-to-End Curriculum Learning Approach for Autonomous Driving Scenarios

In this work, we combine Curriculum Learning with Deep Reinforcement Learning to learn without any prior domain knowledge, an end-to-end competitive driving policy for the CARLA autonomous driving simulator. To our knowledge, we are the first to …

CIOD:an intelligent class-incremental object detection system with nearest mean of exemplars

Object detection has been widely used in intelligent video surveillance, robot navigation, industrial detection, and other fields. Object detection can effectively reduce the consumption of human capital and has important practical significance. …

Emotion recognition by web-shaped model

Emotions recognition is widely applied for many tasks in different fields, from human-computer and human-robot interaction to learning platforms. Also, it can be used as an intrinsic approach for face recognition tasks, in which an …

Fully-automated deep learning pipeline for segmentation and classification of breast ultrasound images

Breast cancer is the most prevalent type of cancer among the female world population. Its early detection has a crucial role in enhancing the effectiveness of treatments, as well as reducing serious complications and deaths. Ultrasound imaging …