18 documents found, page 1 of 2
Sentiment Analysis in Portuguese Restaurant Reviews: Application of Transformer...
Branco, Alexandre; Parada, Daniel; Silva, Marcos; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoThis study focuses on improving sentiment analysis in restaurant reviews by leveraging transfer learning and transformer-based pre-trained models. This work evaluates the suitability of pre trained deep learning models for analyzing Natural Language Processing tasks in Portuguese. It also explores the viability of utilizing edge devices for Natural Language Processing tasks, considering their computational limi...
Machine learning system for commercial banana harvesting
Hayat, Ahatsham; Baglat, Preety; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando Morgado; Baglat, Preety; Silva Mendonça, Fábio Rúben<jats:title>Abstract</jats:title> <jats:p>The conventional process of visual detection and manual harvesting of the banana bunch has been a known problem faced by the agricultural industry. It is a laborious activity associated with inconsistency in the inspection and grading process, leading to post-harvest losses. Automated fruit harvesting using computer vision empowered by deep learning could significantly ...
Sleep Analysis by Evaluating the Cyclic Alternating Pattern A Phases
Alves, Arturo; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoSleep is a complex process divided into different stages, and a decrease in sleep quality can lead to adverse health-related effects. Therefore, diagnosing and treating sleep-related conditions is crucial. The Cyclic Alternating Pattern (CAP) is an indicator of sleep instability and can assist in assessing sleep-related disorders such as sleep apnea. However, manually detecting CAP-related events is time-consum...
Towards automatic EEG cyclic alternating pattern analysis: a systematic review
Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando Morgado; Ravelo-García, Antonio G.; Rosenzweig, IvanaThis study conducted a systematic review to determine the feasibility of automatic Cyclic Alternating Pattern (CAP) analysis. Specifically, this review followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to address the formulated research question: is automatic CAP analysis viable for clinical applica tion? From the identified 1,280 articles, the review inclu...
The Potential of Machine Learning for Wind Speed and Direction Short-Term Forec...
Alves, Décio; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoWind forecasting, which is essential for numerous services and safety, has significantly improved in accuracy due to machine learning advancements. This study reviews 23 articles from 1983 to 2023 on machine learning for wind speed and direction nowcasting. The wind prediction ranged from 1 min to 1 week, with more articles at lower temporal resolutions. Most works employed neural networks, focusing recently on...
Novel Comparative Study for the Detection of COVID-19 Using CT Scan and Chest X...
Hayat, Ahatsham; Baglat, Preety; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoThe number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic continues, with new variants constantly emerging. Therefore, to prevent the virus from spreading, coronavirus cases must be diagnosed as soon as possible. The COVID-19 pandemic has had a devastating impact on people’s health and the economy worldwide. For COVID-19 detection, reverse transcription-polymerase chain reaction te...
Non-Destructive Banana Ripeness Detection Using Shallow and Deep Learning: A Sy...
Baglat, Preety; Hayat, Ahatsham; Mendonça, Fábio; Gupta, Ankit; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoThe ripeness of bananas is the most significant factor affecting nutrient composition and demand. Conventionally, cutting and ripeness analysis requires expert knowledge and substantial human intervention, and different studies have been conducted to automate and substantially reduce human effort. Using the Preferred Reporting Items for the Systematic Reviews approach, 1548 studies were extracted from journals ...
Automated Aviation Wind Nowcasting: Exploring Feature-Based Machine Learning Me...
Alves, Décio; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoWind factors significantly influence air travel, and extreme conditions can cause operational disruptions. Machine learning approaches are emerging as a valuable tool for predicting wind pat terns. This research, using Madeira International Airport as a case study, delves into the effectiveness of feature creation and selection for wind nowcasting, focusing on predicting wind speed, direction, and gusts. Data f...
On the Use of Kullback–Leibler Divergence for Kernel Selection and Interpretati...
Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando Morgado; Ravelo-García, Antonio G.This study presents a novel approach for kernel selection based on Kullback–Leibler divergence in variational autoencoders using features generated by the convolutional encoder. The proposed methodology focuses on identifying the most relevant subset of latent variables to reduce the model’s parameters. Each latent variable is sampled from the distribution associated with a single kernel of the last encoder’s c...
On the Use of Transformer-Based Models for Intent Detection Using Clustering Al...
Moura, André; Lima, Pedro; Mendonça, Fábio; Mostafa, Sheikh Shanawaz; Dias, Fernando MorgadoChatbots are becoming increasingly popular and require the ability to interpret natural language to provide clear communication with humans. To achieve this, intent detection is cru cial. However, current applications typically need a significant amount of annotated data, which is time-consuming and expensive to acquire. This article assesses the effectiveness of different text representations for annotating un...