Search Results for author: Eduardo Todt

Found 10 papers, 8 papers with code

DACov: A Deeper Analysis of Data Augmentation on the Computed Tomography Segmentation Problem

1 code implementation10 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.

Computed Tomography (CT) Data Augmentation +1

Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT's Semantic Segmentation

1 code implementation19 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.

Computed Tomography (CT) Data Augmentation +1

Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT's Semantic Segmentation

1 code implementation30 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.

Computed Tomography (CT) Semantic Segmentation

BEyond observation: an approach for ObjectNav

1 code implementation21 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.

Autonomous Navigation Simultaneous Localization and Mapping

IDA: Improved Data Augmentation Applied to Salient Object Detection

1 code implementation18 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.

Data Augmentation Image Cropping +4

For the Thrill of it All: A bridge among Linux, Robot Operating System, Android and Unmanned Aerial Vehicles

1 code implementation20 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

Can Giraffes Become Birds? An Evaluation of Image-to-image Translation for Data Generation

no code implementations10 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.

Image-to-Image Translation Translation

Masking Salient Object Detection, a Mask Region-based Convolutional Neural Network Analysis for Segmentation of Salient Objects

no code implementations17 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.

object-detection RGB Salient Object Detection +1

An Efficient and Layout-Independent Automatic License Plate Recognition System Based on the YOLO detector

1 code implementation4 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.

Data Augmentation License Plate Detection +2

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