15 citations · 35 across the 11 of their papers we have counts for
12 papers
An Ensemble-Based Self-Taught Learning Approach for Parking Space Classification Under Limited Data
Lucas de Oliveira Cunha, Joelton Deonei Gotz, Paulo Lisboa de Almeida +1
Parking spot classification is a fundamental task in intelligent transportation systems, yet most deep learning approaches rely on large amounts of annotated data and exhibit limit…
Generalizable Brain Tumor Segmentation with Self-Training and Tumor-Aware Deformations
Henrique Zan Grande, Jeovane Honorio Alves, Rayson Laroca +1
This work presents an approach to the Generalizability Across Tumors (BraTS-GoAT) task of the BraTS 2026 Challenge, which focuses on robust segmentation of brain tumor sub-regions…
Audio-Text Cross-Attention with Psycholinguistic Support Features for Ambivalence/Hesitancy Recognition
Luiz F. B. F. Martins, Rodrigo W. Pisaia, Matheus M. Girardi +5
We present a frame-independent audio-text system for the 3rd Ambivalence/Hesitancy Video Recognition Challenge at the 11th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop…
On the Role of MRI Sequences in Cross-Dataset Generalization for Brain Tumor Segmentation
Henrique Zan Grande, João G. Pitol, Lucas B. Schuck +3
Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learning architectures such as U-N…
Optimizing Parking Space Classification: Distilling Ensembles into Lightweight Classifiers
Paulo Luza Alves, André Hochuli, Luiz Eduardo de Oliveira +1
When deploying large-scale machine learning models for smart city applications, such as image-based parking lot monitoring, data often must be sent to a central server to perform c…
Deep Single Models vs. Ensembles: Insights for a Fast Deployment of Parking Monitoring Systems
Andre Gustavo Hochuli, Jean Paul Barddal, Gillian Cezar Palhano +2
Searching for available parking spots in high-density urban centers is a stressful task for drivers that can be mitigated by systems that know in advance the nearest parking space…
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…
Evaluation of Different Annotation Strategies for Deployment of Parking Spaces Classification Systems
Andre G. Hochuli, Alceu S. Britto, Paulo R. L. de Almeida +2
When using vision-based approaches to classify individual parking spaces between occupied and empty, human experts often need to annotate the locations and label a training set con…
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…
A Comprehensive Comparison of End-to-End Approaches for Handwritten Digit String Recognition
Andre G. Hochuli, Alceu S. Britto, David A. Saji +3
Over the last decades, most approaches proposed for handwritten digit string recognition (HDSR) have resorted to digit segmentation, which is dominated by heuristics, thereby impos…
An End-to-End Approach for Recognition of Modern and Historical Handwritten Numeral Strings
Andre G. Hochuli, Alceu S. Britto, Jean P. Barddal +2
An end-to-end solution for handwritten numeral string recognition is proposed, in which the numeral string is considered as composed of objects automatically detected and recognize…
Segmentation-Free Approaches for Handwritten Numeral String Recognition
Andre G Hochuli, Luiz E S Oliveira, Alceu S Britto +1
This paper presents segmentation-free strategies for the recognition of handwritten numeral strings of unknown length. A synthetic dataset of touching numeral strings of sizes 2-,…