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 across a heterogeneous patient population. The proposed method employs the nnU-Net framework with a large residual encoder architecture, int...
Henrique Zan Grande, Jeovane Honorio Alves, R. Laroca et al.· 0 citations
Vehicle attribute analysis is a key component of Intelligent Transportation Systems (ITS), supporting applications such as vehicle identification, traffic monitoring, and forensic investigation. However, models trained under controlled conditions often degrade in real surveillance scenarios due to changes in viewpoint,...
S. Silva, Otavio T. Remer, G. E. Lima et al.· 0 citations
Vehicle attribute recognition is an important task in intelligent transportation systems, particularly when Automatic License Plate Recognition (ALPR) is unavailable or unreliable. Although vision foundation models have shown strong transferability across domains, their effectiveness for fine-grained vehicle classifica...
Alexandre V. Delazeri, G. E. Lima, E. Nascimento et al.· 0 citations
A confidence-aware ensemble that combines SVTRv2, PARSeq, and MAERec after fine-tuning on the official training split is proposed, and an error analysis of all remaining mistakes shows that 48% are associated with labeling issues, visual ambiguity, or illegible samples, highlighting the value of diagnostic reporting fo...
L. A. Dias, Henrique A. Schulz, Rafael Tadeu Machado de Miranda et al.· 0 citations
The results show that clean-set performance is not a reliable indicator of robustness under compression, resizing, and blurring, and reinforce the need for degraded evaluation protocols and highlight self-supervised visual representations as a promising direction for robust face forgery detection.
L. Cunha, Lucas Sotomaior, Lucas Gasperin et al.· 0 citations
This study systematically evaluates how individual MRI sequences influence model robustness across two well-known datasets, and shows that the T2f/FLAIR sequence achieves the best cross-dataset performance, with Dice scores exceeding 75%.
Henrique Zan Grande, João G. Pitol, Lucas B. Schuck et al.· 0 citations
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, ranked third overall on the official challenge leaderboard.
L. F. B. F. Martins, Rodrigo W. Pisaia, M. Girardi et al.· arXiv.org· 1 citation
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