1 citations · 2 across the 7 of their papers we have counts for
9 papers · 1 filter
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…