1 code implementation • 10 Mar 2023 • Bruno A. Krinski, Daniel V. Ruiz, Rayson Laroca, Eduardo Todt
Our findings show that GAN-based techniques and spatial-level transformations are the most promising for improving the learning of deep models on this problem, with the StarGANv2 + F with a probability of 0. 3 achieving the highest F-score value on the Ricord1a dataset in the unified training strategy.
1 code implementation • 19 May 2022 • Bruno A. Krinski, Daniel V. Ruiz, Eduardo Todt
In this work, we propose an extensive analysis of how different data augmentation techniques improve the training of encoder-decoder neural networks on this problem.
1 code implementation • 30 Sep 2021 • Bruno A. Krinski, Daniel V. Ruiz, Eduardo Todt
To the best of our knowledge, this is the largest evaluation in number of encoders, decoders, and datasets proposed in the field of Covid-19 CT segmentation.
1 code implementation • 21 Jun 2021 • Daniel V. Ruiz, Eduardo Todt
With the rise of automation, unmanned vehicles became a hot topic both as commercial products and as a scientific research topic.
1 code implementation • 18 Sep 2020 • Daniel V. Ruiz, Bruno A. Krinski, Eduardo Todt
Combining our method with others surpasses traditional techniques such as horizontal-flip in 0. 52% for F-measure and 1. 19% for Precision.
1 code implementation • 20 Jun 2020 • Daniel V. Ruiz, Leonardo A. Vidal, Eduardo Todt
Civilian Unmanned Aerial Vehicles (UAVs) are becoming more accessible for domestic use.
Signal Processing Robotics
no code implementations • 10 Jan 2020 • Daniel V. Ruiz, Gabriel Salomon, Eduardo Todt
For the quantitative analysis, a pre-trained Mask R-CNN was used for the detection and segmentation of birds on Pascal VOC, Caltech-UCSD Birds 200-2011, and our new dataset entitled FakeSet.
1 code implementation • 3 Oct 2019 • Daniel V. Ruiz, Bruno A. Krinski, Eduardo Todt
We also compared our method with other data augmentation techniques.
no code implementations • 17 Sep 2019 • Bruno A. Krinski, Daniel V. Ruiz, Guilherme Z. Machado, Eduardo Todt
However, there is no extensive comparison between the two networks in the SOD literature endorsing the effectiveness of Mask-RCNNs over FCN when segmenting salient objects.
1 code implementation • 4 Sep 2019 • Rayson Laroca, Luiz A. Zanlorensi, Gabriel R. Gonçalves, Eduardo Todt, William Robson Schwartz, David Menotti
This paper presents an efficient and layout-independent Automatic License Plate Recognition (ALPR) system based on the state-of-the-art YOLO object detector that contains a unified approach for license plate (LP) detection and layout classification to improve the recognition results using post-processing rules.
Ranked #1 on License Plate Recognition on Caltech Cars