Hélder Araújo
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View article: Gestão de pessoas em uma instituição de ensino de jovens e adultos
Gestão de pessoas em uma instituição de ensino de jovens e adultos Open
Este artigo investigou em que medida a gestão de pessoas pode melhorar a satisfação dos educadores e a qualidade do ensino em uma instituição de ensino de jovens e adultos. Os objetivos da pesquisa incluem identificar a percepção dos educa…
View article: Tph-Yolov7t: A Boosted Yolo Transformer Prediction Head for Search and Rescue with Drones
Tph-Yolov7t: A Boosted Yolo Transformer Prediction Head for Search and Rescue with Drones Open
View article: Retention-Yolo: An Ultraboost Yolo Retention Prediction Head for Search and Rescue with Drones
Retention-Yolo: An Ultraboost Yolo Retention Prediction Head for Search and Rescue with Drones Open
View article: A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research
A Survey on Group Fairness in Federated Learning: Challenges, Taxonomy of Solutions and Directions for Future Research Open
Group fairness in machine learning is an important area of research focused on achieving equitable outcomes across different groups defined by sensitive attributes such as race or gender. Federated Learning, a decentralized approach to tra…
View article: SRFDet3D: Sparse Region Fusion based 3D Object Detection
SRFDet3D: Sparse Region Fusion based 3D Object Detection Open
Unlike the earlier 3D object detection approaches that formulate hand-crafted dense (in thousands) object proposals by leveraging anchors on dense feature maps, we formulate np (in hundreds) number of learnable sparse object proposals to p…
View article: TPH-YOLOv7t : A Boosted YOLO Transformer Prediction Head for Search and Rescue with Drones
TPH-YOLOv7t : A Boosted YOLO Transformer Prediction Head for Search and Rescue with Drones Open
In recent years, drones have become a fundamental tool for searching for missing persons in the wild and at sea by collecting aerial images. Search and Rescue operators inspect these images in real-time, aiming to spot the missing persons.…
View article: DeLiVoTr: Deep and light-weight voxel transformer for 3D object detection
DeLiVoTr: Deep and light-weight voxel transformer for 3D object detection Open
The image-based backbone (feature extraction) networks downsample the feature maps not only to increase the receptive field but also to efficiently detect objects of various scales. The existing feature extraction networks in LiDAR-based 3…
View article: Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning
Unveiling Group-Specific Distributed Concept Drift: A Fairness Imperative in Federated Learning Open
In the evolving field of machine learning, ensuring group fairness has become a critical concern, prompting the development of algorithms designed to mitigate bias in decision-making processes. Group fairness refers to the principle that a…
View article: Local Forward-Motion Panoramic Views for Localization and Lesion Detection for Multi-Camera Wireless Capsule Endoscopy Videos
Local Forward-Motion Panoramic Views for Localization and Lesion Detection for Multi-Camera Wireless Capsule Endoscopy Videos Open
View article: Li3DeTr: A LiDAR based 3D Detection Transformer
Li3DeTr: A LiDAR based 3D Detection Transformer Open
Inspired by recent advances in vision transformers for
\nobject detection, we propose Li3DeTr, an end-to-end LiDAR
\nbased 3D Detection Transformer for autonomous driving,
\nthat inputs LiDAR point clouds and regresses 3D bounding
\nboxes.…
View article: FAIR-FATE: Fair Federated Learning with Momentum
FAIR-FATE: Fair Federated Learning with Momentum Open
While fairness-aware machine learning algorithms have been
\nreceiving increasing attention, the focus has been on centralized machine
\nlearning, leaving decentralized methods underexplored. Federated
\nLearning is a decentralized form of…
View article: FITTING A NORMAL PROBABILITY DISTRIBUTION TO DEPTH ESTIMATIONS OF THREE REALSENSE™ RGB-D CAMERAS TESTED IN SCENES WITH TRANSPARENCY
FITTING A NORMAL PROBABILITY DISTRIBUTION TO DEPTH ESTIMATIONS OF THREE REALSENSE™ RGB-D CAMERAS TESTED IN SCENES WITH TRANSPARENCY Open
In the last decade, various companies have released different versions of RGB-D sensors, improving their performance at various levels (resolution, frame rate, robustness). These devices can measure depth using one of the following optical…
View article: MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving
MSF3DDETR: Multi-Sensor Fusion 3D Detection Transformer for Autonomous Driving Open
3D object detection is a significant task for autonomous driving. Recently with the progress of vision transformers, the 2D object detection problem is being treated with the set-to-set loss. Inspired by these approaches on 2D object detec…
View article: Li3DeTr: A LiDAR based 3D Detection Transformer
Li3DeTr: A LiDAR based 3D Detection Transformer Open
Inspired by recent advances in vision transformers for object detection, we propose Li3DeTr, an end-to-end LiDAR based 3D Detection Transformer for autonomous driving, that inputs LiDAR point clouds and regresses 3D bounding boxes. The LiD…
View article: An Experimental Assessment of Depth Estimation in Transparent and Translucent Scenes for Intel RealSense D415, SR305 and L515
An Experimental Assessment of Depth Estimation in Transparent and Translucent Scenes for Intel RealSense D415, SR305 and L515 Open
RGB-D cameras have become common in many research fields since these inexpensive devices provide dense 3D information from the observed scene. Over the past few years, the RealSense™ range from Intel® has introduced new, cost-effective RGB…
View article: FAIR-FATE: Fair Federated Learning with Momentum
FAIR-FATE: Fair Federated Learning with Momentum Open
While fairness-aware machine learning algorithms have been receiving increasing attention, the focus has been on centralized machine learning, leaving decentralized methods underexplored. Federated Learning is a decentralized form of machi…
View article: FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes
FAWOS: Fairness-Aware Oversampling Algorithm Based on Distributions of Sensitive Attributes Open
With the increased use of machine learning algorithms to make decisions which impact people's
\nlives, it is of extreme importance to ensure that predictions do not prejudice subgroups of the population with
\nrespect to sensitive attribut…
View article: Intel RealSense SR305, D415 and L515: Experimental Evaluation and Comparison of Depth Estimation
Intel RealSense SR305, D415 and L515: Experimental Evaluation and Comparison of Depth Estimation Open
View article: Registration of Consecutive Frames From Wireless Capsule Endoscopy for 3D Motion Estimation
Registration of Consecutive Frames From Wireless Capsule Endoscopy for 3D Motion Estimation Open
Wireless Capsule Endoscopy (WCE) is a non-invasive medical procedure devised for painless
\nin vivo inspection of the gastrointestinal (GI) tract. It is especially valuable for the examination of the small
\nintestine since it is dif cult …
View article: Object Detection in Traffic Scenarios - A Comparison of Traditional and Deep Learning Approaches
Object Detection in Traffic Scenarios - A Comparison of Traditional and Deep Learning Approaches Open
In the area of computer vision, research on object detection algorithms has grown rapidly as it is the fundamental step for automation, specifically for self-driving vehicles.This work presents a comparison of traditional and deep learning…
View article: Quantitative Evaluation of Endoscopic SLAM Methods: EndoSLAM Dataset.
Quantitative Evaluation of Endoscopic SLAM Methods: EndoSLAM Dataset. Open
Deep learning techniques hold promise to improve dense topography reconstruction and pose estimation, as well as simultaneous localization and mapping (SLAM). However, currently available datasets do not support effective quantitative benc…
View article: EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner
EndoSLAM Dataset and An Unsupervised Monocular Visual Odometry and Depth Estimation Approach for Endoscopic Videos: Endo-SfMLearner Open
Deep learning techniques hold promise to develop dense topography reconstruction and pose estimation methods for endoscopic videos. However, currently available datasets do not support effective quantitative benchmarking. In this paper, we…
View article: Dynamic Obstacle Detection in Traffic Environments
Dynamic Obstacle Detection in Traffic Environments Open
The research on autonomous vehicles has grown increasingly with the advent of neural networks. Dynamic obstacle detection is a fundamental step for self-driving vehicles in traffic environments. This paper presents a comparison of state-of…
View article: Learning to Navigate Endoscopic Capsule Robots
Learning to Navigate Endoscopic Capsule Robots Open
Deep reinforcement learning (DRL) techniques have been successful in several domains, such as physical simulations, computer games, and simulated robotic tasks, yet the transfer of these successful learning concepts from simulations into t…
View article: Magnetic- Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots
Magnetic- Visual Sensor Fusion-based Dense 3D Reconstruction and Localization for Endoscopic Capsule Robots Open
Reliable and real-time 3D reconstruction and localization functionality is a crucial prerequisite for the navigation of actively controlled capsule endoscopic robots as an emerging, minimally invasive diagnostic and therapeutic technology …
View article: EndoSensorFusion: Particle Filtering-Based Multi-Sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots
EndoSensorFusion: Particle Filtering-Based Multi-Sensory Data Fusion with Switching State-Space Model for Endoscopic Capsule Robots Open
A reliable, real time multi-sensor fusion functionality is crucial for localization of actively controlled capsule endoscopy robots, which are an emerging, minimally invasive diagnostic and therapeutic technology for the gastrointestinal (…
View article: Robustified Structure from Motion with rolling-shutter camera using straightness constraint
Robustified Structure from Motion with rolling-shutter camera using straightness constraint Open
View article: Biologically inspired computational modeling of motion based on middle temporal area
Biologically inspired computational modeling of motion based on middle temporal area Open
This paper describes a bio-inspired algorithm for motion computation based on V1 (Primary Visual Cortex) andMT (Middle Temporal Area) cells. The behavior of neurons in V1 and MT areas contain significant information to understand the perce…
View article: Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and\n Localization for Endoscopic Capsule Robots
Magnetic-Visual Sensor Fusion-based Dense 3D Reconstruction and\n Localization for Endoscopic Capsule Robots Open
Reliable and real-time 3D reconstruction and localization functionality is a\ncrucial prerequisite for the navigation of actively controlled capsule\nendoscopic robots as an emerging, minimally invasive diagnostic and therapeutic\ntechnolo…
View article: Sparse-then-dense alignment-based 3D map reconstruction method for endoscopic capsule robots
Sparse-then-dense alignment-based 3D map reconstruction method for endoscopic capsule robots Open