534 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Universidade Federal do ParanáBR22 papers
- Centre National de la Recherche ScientifiqueFR19 papers
- Université Savoie Mont BlancFR18 papers
- Laboratoire Optimisation de la Conception et Ingénierie de l'EnvironnementFR16 papers
- Le LAMAFR15 papers
- Institut National des Sciences Mathématiques et de leurs InteractionsFR9 papers
- Universidade Tecnológica Federal do ParanáBR7 papers
- Universidade Estadual de LondrinaBR6 papers
- École de Technologie SupérieureCA4 papers
- Instituto Federal do ParanáBR4 papers
- Instituto Federal de Educação, Ciência e Tecnologia de Santa CatarinaBR3 papers
- Laboratoire de Mathématiques Blaise PascalFR3 papers
66 papers
Robust Face Super-Resolution and Recognition Through Multi-Feature Aggregation in Diffusion Models
Marcelo dos Santos, Rayson Laroca, João Carlos Raposo Neves +1
Images acquired in surveillance environments often suffer from conditions such as low resolution, variations in pose, irregular illumination, and occlusions. Due to the low quality…
Toward Unified Fine-Grained Vehicle Classification and Automatic License Plate Recognition
Gabriel E. Lima, Valfride Nascimento, Eduardo Santos +3
Extracting vehicle information from surveillance images is essential for intelligent transportation systems, enabling applications such as traffic monitoring and criminal investiga…
Além do Desempenho: Um Estudo da Confiabilidade de Detectores de Deepfakes
Lucas Lopes, Rayson Laroca, André Grégio
Deepfakes are synthetic media generated by artificial intelligence, with positive applications in education and creativity, but also serious negative impacts such as fraud, misinfo…
Advancing Multinational License Plate Recognition Through Synthetic and Real Data Fusion: A Comprehensive Evaluation
Rayson Laroca, Valter Estevam, Gladston J. P. Moreira +2
Automatic License Plate Recognition is a frequent research topic due to its wide-ranging practical applications. While recent studies use synthetic images to improve License Plate…
IncA-DES: An incremental and adaptive dynamic ensemble selection approach using online K-d tree neighborhood search for data streams with concept drift
Eduardo V. L. Barboza, Paulo R. Lisboa de Almeida, Alceu de Souza Britto +2
Data streams pose challenges not usually encountered in batch-based ML. One of them is concept drift, which is characterized by the change in data distribution over time. Among man…
Toward Advancing License Plate Super-Resolution in Real-World Scenarios: A Dataset and Benchmark
Valfride Nascimento, Gabriel E. Lima, Rafael O. Ribeiro +3
Recent advancements in super-resolution for License Plate Recognition (LPR) have sought to address challenges posed by low-resolution (LR) and degraded images in surveillance, traf…
Improving Small Drone Detection Through Multi-Scale Processing and Data Augmentation
Rayson Laroca, Marcelo dos Santos, David Menotti
Detecting small drones, often indistinguishable from birds, is crucial for modern surveillance. This work introduces a drone detection methodology built upon the medium-sized YOLOv…
Temporal Analysis of Drifting Hashtags in Textual Data Streams: A Graph-Based Application
Cristiano M. Garcia, Alceu de Souza Britto, Jean Paul Barddal
Initially supported by Twitter, hashtags are now used on several social media platforms. Hashtags are helpful for tagging, tracking, and grouping posts on similar topics. In this p…
Concept Drift Adaptation in Text Stream Mining Settings: A Systematic Review
Cristiano Mesquita Garcia, Ramon Simoes Abilio, Alessandro Lameiras Koerich +2
The society produces textual data online in several ways, e.g., via reviews and social media posts. Therefore, numerous researchers have been working on discovering patterns in tex…
Random Forest Kernel for High-Dimension Low Sample Size Classification
Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal +1
High dimension, low sample size (HDLSS) problems are numerous among real-world applications of machine learning. From medical images to text processing, traditional machine learnin…
Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis
Jeovane Honório Alves, Horácio A. C. G. Pedroso, Rafael Honorio Venetikides +4
The growing use of digital communication platforms has given rise to various criminal activities, such as grooming and drug dealing, which pose significant challenges to law enforc…
Vehicle Occurrence-based Parking Space Detection
Paulo R. Lisboa de Almeida, Jeovane Honório Alves, Luiz S. Oliveira +3
Smart-parking solutions use sensors, cameras, and data analysis to improve parking efficiency and reduce traffic congestion. Computer vision-based methods have been used extensivel…
Advances on Concept Drift Detection in Regression Tasks using Social Networks Theory
Jean Paul Barddal, Heitor Murilo Gomes, Fabrício Enembreck
Mining data streams is one of the main studies in machine learning area due to its application in many knowledge areas. One of the major challenges on mining data streams is concep…
Do We Train on Test Data? The Impact of Near-Duplicates on License Plate Recognition
Rayson Laroca, Valter Estevam, Alceu S. Britto +2
This work draws attention to the large fraction of near-duplicates in the training and test sets of datasets widely adopted in License Plate Recognition (LPR) research. These dupli…
A Systematic Review on Computer Vision-Based Parking Lot Management Applied on Public Datasets
Paulo Ricardo Lisboa de Almeida, Jeovane Honório Alves, Rafael Stubs Parpinelli +1
Computer vision-based parking lot management methods have been extensively researched upon owing to their flexibility and cost-effectiveness. To evaluate such methods authors often…
A Survey on Concept Drift in Process Mining
Denise Maria Vecino Sato, Sheila Cristiana de Freitas, Jean Paul Barddal +1
Concept drift in process mining (PM) is a challenge as classical methods assume processes are in a steady-state, i.e., events share the same process version. We conducted a systema…
Dense Video Captioning Using Unsupervised Semantic Information
Valter Estevam, Rayson Laroca, Helio Pedrini +1
We introduce a method to learn unsupervised semantic visual information based on the premise that complex events can be decomposed into simpler events and that these simple events…
An efficient two-dimensional heat transfer model for building envelopes
Julien Berger, Suelen Gasparin, Walter Mazuroski +1
A two-dimensional model is proposed for energy efficiency assessment through the simulation of heat transfer in building envelopes, considering the influence of the surrounding env…
Open-set Face Recognition for Small Galleries Using Siamese Networks
Gabriel Salomon, Alceu Britto, Rafael H. Vareto +2
Face recognition has been one of the most relevant and explored fields of Biometrics. In real-world applications, face recognition methods usually must deal with scenarios where no…
End-to-End Approach for Recognition of Historical Digit Strings
Mengqiao Zhao, Andre G. Hochuli, Abbas Cheddad
The plethora of digitalised historical document datasets released in recent years has rekindled interest in advancing the field of handwriting pattern recognition. In the same vein…
Leveraging Data Scientists and Business Expectations During the COVID-19 Pandemic
Wellington Rodrigo Monteiro, Marcio Leandro do Prado, Gilberto Reynoso-Meza
The COVID-19 pandemic presented itself as a challenge for separate societal sectors. On the information technology (IT) standpoint, it does include the maintenance of the infrastru…
A New Periocular Dataset Collected by Mobile Devices in Unconstrained Scenarios
Luiz A. Zanlorensi, Rayson Laroca, Diego R. Lucio +3
Recently, ocular biometrics in unconstrained environments using images obtained at visible wavelength have gained the researchers' attention, especially with images captured by mob…
scikit-dyn2sel -- A Dynamic Selection Framework for Data Streams
Lucca Portes Cavalheiro, Jean Paul Barddal, Alceu de Souza Britto +1
Mining data streams is a challenge per se. It must be ready to deal with an enormous amount of data and with problems not present in batch machine learning, such as concept drift.…
Short-term forecasting COVID-19 cumulative confirmed cases: Perspectives for Brazil
Matheus Henrique Dal Molin Ribeiro, Ramon Gomes da Silva, Viviana Cocco Mariani +1
The new Coronavirus (COVID-19) is an emerging disease responsible for infecting millions of people since the first notification until nowadays. Developing efficient short-term fore…