11 documents found, page 1 of 2
The Synergy between artificial intelligence, remote sensing, and archaeological...
Canedo, Daniel; Hipólito, João; Fonte, João; Dias, Rita; Pereiro, Tiago do; Georgieva, Petia; Gonçalves-Seco, Luís; Vázquez, Marta; Pires, NelsonThe increasing relevance of remote sensing and artificial intelligence (AI) for archaeological research and cultural heritage management is undeniable. However, there is a critical gap in this field. Many studies conclude with identifying hundreds or even thousands of potential sites, but very few follow through with crucial fieldwork validation to confirm their existence. This research addresses this gap by pr...
Automated detection of hillforts in remote sensing imagery with deep multimodal...
Canedo, Daniel; Fonte, João; Dias, Rita; Pereiro, Tiago do; Gonçalves‐Seco, Luís; Vázquez, Marta; Georgieva, Petia; Neves, António J. R.Recent advancements in remote sensing and artificial intelligence can potentially revolutionize the automated detection of archaeological sites. However, the challenging task of interpreting remote sensing imagery combined with the intricate shapes of archaeological sites can hinder the performance of computer vision systems. This work presents a computer vision system trained for efficient hillfort detection i...
Uncovering archaeological sites in airborne LiDAR data with data-centric artifi...
Canedo, Daniel; Fonte, João; Seco, Luis Gonçalves; Vázquez, Marta; Dias, Rita; Pereiro, Tiago Do; Hipólito, João; Menéndez-Marsh, FernandoMapping potential archaeological sites using remote sensing and artificial intelligence can be an efficient tool to assist archaeologists during project planning and fieldwork. This paper explores the use of airborne LiDAR data and data-centric artificial intelligence for identifying potential burial mounds. The challenge of exploring the landscape and mapping new archaeological sites, coupled with the difficul...
AI-powered management of identity photos for institutional staff directories
Canedo, Daniel; Vieira, José; Gonçalves, António; Neves, Antonio J. R.The recent developments in Deep Learning and Computer Vision algorithms allow the automation of several tasks which up until that point required the allocation of considerable human resources. One task that is getting behind the recent developments is the management of identity photos for institutional staff directories because it deals with sensitive information, namely the association of a photo to a person. ...
Uncovering archaeological sites in airborne LiDAR data with data-centric artifi...
Canedo, Daniel; Fonte, João; Seco, Luis Gonçalves; Vázquez, Marta; Dias, Rita; Pereiro, Tiago do; Hipólito, João; Menéndez-Marsh, FernandoMapping potential archaeological sites using remote sensing and artificial intelligence can be an efficient tool to assist archaeologists during project planning and fieldwork. This paper explores the use of airborne LiDAR data and data-centric artificial intelligence for identifying potential burial mounds. The challenge of exploring the landscape and mapping new archaeological sites, coupled with the difficul...
An innovative vision system for floor-cleaning robots based on YOLOv5
Canedo, Daniel; Fonseca, Pedro; Georgieva, Petia; Neves, António J. R.The implementation of a robust vision system in floor-cleaning robots enables them to optimize their navigation and analysing the surrounding floor, leading to a reduction on power, water and chemical products’ consumption. In this paper, we propose a novel pipeline of a vision system to be integrated into floor-cleaning robots. This vision system was built upon the YOLOv5 framework, and its role is to detect d...
A deep learning-based dirt detection computer vision system for floor-cleaning ...
Canedo, Daniel; Fonseca, Pedro; Georgieva, Petia; Neves, António J. R.Floor-cleaning robots are becoming increasingly more sophisticated over time and with the addition of digital cameras supported by a robust vision system they become more autonomous, both in terms of their navigation skills but also in their capabilities of analyzing the surrounding environment. This document proposes a vision system based on the YOLOv5 framework for detecting dirty spots on the floor. The purp...
The impact of pre-processing algorithms in facial expression recognition
Canedo, Daniel; Neves, António J. R.This paper proposes several pre-processing algorithms to improve facial expression recognition based on Convolutional Neural Networks (CNNs) models. The proposed CNN model was trained on the Extended Cohn-Kanade dataset (CK+) after applying the pre-processing stages and achieved competitive results (93.90% recognition accuracy) despite its simple and light architecture. Using this CNN model, a study on the impa...
Facial expression recognition using computer vision: a systematic review
Canedo, Daniel; Neves, António J. R.Emotion recognition has attracted major attention in numerous fields because of its relevant applications in the contemporary world: marketing, psychology, surveillance, and entertainment are some examples. It is possible to recognize an emotion through several ways; however, this paper focuses on facial expressions, presenting a systematic review on the matter. In addition, 112 papers published in ACM, IEEE, B...
Focus estimation in academic environments using Computer Vision
Canedo, Daniel; Trifan, Alina; Neves, António J. R.In this paper we propose a system capable of monitoring students’ focus through cameras and using Computer Vision algorithms. Experimental results show that our system is capable of identifying students and tracking their focus during a class. At the end of the class, the system outputs graphical feedback to teachers regarding the average level of students’ focus. Moreover, it can identify lecture periods in wh...