André O. Françani

13 papers C 1Journal 8Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Transformer-Based Model for Monocular Visual Odometry: A Video Understanding Approach.
IEEE Access
André O. Françani, Marcos R. O. A. Máximo
2024 J jnl
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning.
CoRR
André O. Françani, Marcos R. O. A. Máximo
2023 — conf
An Instance Segmentation Dataset of Yeast Cells in Microstructures.
EMBC
Christoph Reich, Tim Prangemeier, André O. Françani, Heinz Koeppl
2023 J jnl
An Instance Segmentation Dataset of Yeast Cells in Microstructures.
CoRR
Christoph Reich, Tim Prangemeier, André O. Françani, Heinz Koeppl
2023 — conf
Motion Consistency Loss for Monocular Visual Odometry with Attention-Based Deep Learning.
LARS/SBR/WRE
André O. Françani, Marcos Ricardo Omena de Albuquerque Máximo
2023 J jnl
Transformer-based model for monocular visual odometry: a video understanding approach.
CoRR
André O. Françani, Marcos R. O. A. Máximo
2022 J jnl
Analysis of the performance of U-Net neural networks for the segmentation of living cells.
CoRR
André O. Françani
2022 — conf
Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry.
LARS/SBR/WRE
André O. Françani, Marcos R. O. de A. Máximo
2022 J jnl
Dense Prediction Transformer for Scale Estimation in Monocular Visual Odometry.
CoRR
André O. Françani, Marcos R. O. A. Máximo
2022 J jnl
Yeast cell segmentation in microstructured environments with deep learning.
Biosyst.
Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl
2021 — conf
Performance Comparison of Convolutional Neural Network Models for Object Detection in Tethered Balloon Imagery.
LARS/SBR/WRE
Débora F. Dos Santos, André O. Françani, Marcos R. O. A. Máximo, Arthur S. C. Ferreira
2020 C conf
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning.
CIBCB
Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl
2020 J jnl
Multiclass Yeast Segmentation in Microstructured Environments with Deep Learning.
CoRR
Tim Prangemeier, Christian Wildner, André O. Françani, Christoph Reich, Heinz Koeppl