94 documents found, page 1 of 10
A genetic algorithm to optimize the dispatch of firefighting resources
Matos, Marina A.; Gonçalves, Rui; Rocha, Ana Maria A. C.; Costa, Lino; Alvelos, Filipe Pereira eThe significant increase in the number of forest fires has raised great interest in studying ways to decrease this number and optimization is one of the most used techniques. This type of methods allows the support of the combat means in fighting forest fires, improving the effectiveness and speed of the firefighters actions. Knowing how many and which resources to allocate to each fire is an important key to s...
Impact of hyper-parameter tuning on CNN accuracy in agricultural image classifi...
Mendes, João; Lima, José; Costa, Lino; Hendrix, Eligius M.T.; Pereira, Ana I.This study explores the impact of hyper-parameter optimization on the performance of convolutional neural networks (CNNs) for olive cultivar classification using transfer learning. Pre-trained ImageNet models such as VGG16, InceptionV3, and ResNet50 were adapted to a proprietary dataset, with VGG16 selected for detailed evaluation. Key hyper-parameters, including layer count, neurons per layer, dropout rate, le...
Preliminary deep-sea data analysis collected at Gloria seamount, Azores-Biscay ...
Tojeira, Inês; Pinto Ribeiro, Luísa; Rafael, Teresa; Albuquerque, Mónica; Simões, Maria; Calado, António; Afonso, Andreia; Ramos, Bruno; Souto, MiguelThe present study provides the first results of the exploratory research campaign to Gloria seamount (summit at 45.03°N, 15.54°W), a newly identified seamount in the NE Atlantic. New multibeam bathymetry and an 8 h remote operated vehicle footage and photography data were compiled and analyzed to give the first insights on the geological nature and benthic megafauna assemblages of Gloria seamount. Footage evide...
Deep learning networks for olive cultivar identification: a comprehensive analy...
Mendes, João; Lima, José; Costa, Lino; Rodrigues, Nuno; Pereira, Ana I.Deep learning networks, more specifically convolutional neural networks, have shown a notable distinction when it comes to computer vision problems. Their versatility spans various domains, where they are applied for tasks such as classification and regression, contingent primarily on the availability of a representative dataset. This work explores the feasibility of employing this approach in the domain of agr...
Optimizing Olive Disease Classification Through Hybrid Machine Learning and Dee...
Mendes, João; Moso, Juliet; Berger, Guido; Lima, José; Costa, Lino; Guessoum, Zahia; Pereira, Ana I.Olive trees play a crucial role in the global agricultural landscape, serving as a primary source of olive oil production. However, olive trees are susceptible to several diseases, which can significantly impact yield and quality. This study addresses the challenge of improving the diagnosis of diseases in olive trees, specifically focusing on aculus olearius and Olive Peacock Spot diseases. Using a novel hybri...
Pest Management in Olive Cultivation Through Computer Vision: A Comparative Stu...
Mendes, João; Berger, Guido; Lima, José; Costa, Lino; Pereira, Ana I.This study compares two computer vision methods to detect yellow sticky traps using unmanned autonomous vehicles in olive tree cultivation. The traps aim to combat and monitor the density of the Bactrocera oleae, an important pest that damages olive fruit, leading to substantial economic losses annually. The evaluation encompassed two distinct methods: firstly, an algorithm employing conventional segmentation t...
An Artificial Intelligence-Based Method to Identify the Stage of Maturation in ...
Mendes, João; Lima, José; Costa, Lino; Rodrigues, Nuno; Leitão, Paulo; Pereira, Ana I.Identifying the maturation stage is an added value for olive oil producers and consumers, whether this is done to predict the best harvest time, give us more information about the olive oil, or even adapt techniques and extraction parameters in the olive oil mill. In this way, the proposed work presents a new method to identify and count the number of olives that enter the mill as well as their stage of maturat...
Performance comparison of NSGA-II and NSGA-III on bi-objective job shop schedul...
Santos, Francisco dos; Costa, Lino; Varela, M.L.R.Job Shop Scheduling (JSS) problems emerge in many industrial sectors, where it is sought to maximize efficiency, minimize costs, minimize energy consumption among other conflicting objectives. Thus, these optimization problems involve two or more objectives. In recent years, new algorithms have been developed and proposed to tackle multiobjective problems such as the Non-dominated Sorting Genetic Algorithm II (...
A firefighting resource dispatch problem optimization using metaheuristics
Matos, Marina A.; Gonçalves, Rui; Rocha, Ana Maria A. C.; Costa, Lino; Alvelos, Filipe Pereira eForest fires are a growing concern in our planet, as they have been increasing in frequency and severity over the last few decades. It is therefore essential to manage firefighting in order to prevent and reduce the damage caused to life, the economy and ecosystems. This work deals with the forest firefighting resource dispatch problem using metaheuristics. It is essential to know when and which suppression res...
Transferable skills development through project-based learning in an industrial...
Carvalho, Violeta; Rodrigues, Cristina Maria Santos; Teixeira, S. F. C. F.; Silva, A. M.; Sousa, Rui M.; Costa, Lino; Alves, Anabela CarvalhoIn the literature, transferable skills refer to the ability to learn and apply knowledge, skills, and attitudes in various professional contexts to solve real-world problems, always taking ethical values into account. Due to job market demands, it becomes imperative to promote these skills in Industrial Engineering and Management (IEM) students, and the active learning strategy Project-Based Learning (PBL) is a...