A5082527457- Advanced Neural Network Applications
- Autonomous Vehicle Technology and Safety
- Robotics and Sensor-Based Localization
- Video Surveillance and Tracking Methods
- Industrial Vision Systems and Defect Detection
- Remote Sensing and LiDAR Applications
- Image and Object Detection Techniques
- Vehicular Ad Hoc Networks (VANETs)
- Cardiovascular Syncope and Autonomic Disorders
- Domain Adaptation and Few-Shot Learning
- Diabetes Treatment and Management
- Biliary and Gastrointestinal Fistulas
- Gallbladder and Bile Duct Disorders
- Renal and Vascular Pathologies
- Advanced X-ray and CT Imaging
- Digital Radiography and Breast Imaging
- Advanced Image and Video Retrieval Techniques
- Robotic Path Planning Algorithms
- Schizophrenia research and treatment
Universidad Carlos III de Madrid
2019-2023
Wirtschaftsförderungsinstitut
2022
Hospital General Universitario Gregorio Marañón
2007
There has been a remarkable increase in prescription rates of antipsychotics children and adolescents recent years. Their side effects are neglected area research this population, despite its vulnerability. In cross-sectional study, we compared the presence 60 who had taken antipsychotic medication for less than 1 month 66 receiving treatment with more 12 months. Mean age total sample was 15.62 years (SD 1.85). Groups did not differ age, gender, or diagnosis. A 21.7% short-term group...
Autonomous vehicles depend on an accurate perception of their surroundings. For this purpose, different approaches are used to detect traffic participants such as cars, cyclists, and pedestrians, well static objects. A commonly method is object detection classification in camera images. However, due the limited field view images, detecting entire environment ego-vehicle additional challenge. Some solutions include use catadioptric cameras or clustered surround systems that require a large...
In this paper, a multi-modal 360° framework for 3D object detection and tracking autonomous vehicles is presented. The process divided into four main stages. First, images are fed CNN network to obtain instance segmentation of the surrounding road participants. Second, LiDAR-to-image association performed estimated mask proposals. Then, isolated points every processed by PointNet ensemble compute their corresponding bounding boxes poses. Lastly, stage based on Unscented Kalman Filter used...
The rapid development of embedded hardware in autonomous vehicles broadens their computational capabilities, thus bringing the possibility to mount more complete sensor setups able handle driving scenarios higher complexity. As a result, new challenges such as multiple detections same object have be addressed. In this work, siamese network is integrated into pipeline well-known 3D detector approach suppress duplicate proposals coming from different cameras via re-identification....
The use of modern LiDAR devices for onboard 3D object detection has paved the road vehicles' full automation. Deep learning approaches leveraging high-resolution spatial data from laser sweeps have become state-of-the-art in field, providing an accurate representation traffic situation. Nonetheless, need a vast amount annotated samples prevents smooth deployment these methods on custom sensor configurations, as differences scene geometry or scanner specifications yield to major performance...
LiDAR devices have become a key sensor for autonomous vehicles perception due to their ability capture reliable geometry information. Indeed, approaches processing data shown an impressive accuracy 3D object detection tasks, outperforming methods solely based on image inputs. However, the wide diversity of on-board configurations makes deployment published algorithms into real platforms hard task, scarcity annotated datasets containing laser scans. We present method generate new point clouds...
This article presents the results of a two-week robot taxi service demonstration in peri-urban and rural areas. A fully robotized Renault Zoe was available for general public use Rambouillet, France. The driving zone included several complex scenarios, such as narrow two-way road, tunnel where lanes reduced from two to one, roundabouts, enabling an evaluation vehicle's capabilities. describes scientific technical development car's perception, navigation, control carry out experiment....
Autonomous driving demands the most reliable perception and navigation technologies. These systems should consider both other agents in road limitations of on-board sensors. Knowing sensor real time allows not only to predict movement but also robustly identify free space road. This paper presents a novel approach that adapts control an autonomous vehicle circumstances specifically challenging scenarios, i.e., roundabouts. The proposal provides visibility map helps system calculate...
In recent years, the field of autonomous driving has witnessed remarkable advancements, driven by integration a multitude sensors, including cameras and LiDAR systems, in different prototypes. However, with proliferation sensor data comes pressing need for more sophisticated information processing techniques. This research paper introduces novel modification to an object detection network that uses camera lidar information, incorporating additional branch designed task re-identifying objects...
The growing on-board processing capabilities have led to more complex sensor configurations, enabling autonomous car prototypes expand their operational scope. Nowadays, the joint use of LiDAR data and multiple cameras is almost a standard poses new challenges for existing multi-modal perception pipelines, such as dealing with contradictory or redundant detections caused by inference on overlapping images. In this paper, we address last issue in context sequential schemes like F-PointNets,...
In this paper, a multi-modal 360$^{\circ}$ framework for 3D object detection and tracking autonomous vehicles is presented. The process divided into four main stages. First, images are fed CNN network to obtain instance segmentation of the surrounding road participants. Second, LiDAR-to-image association performed estimated mask proposals. Then, isolated points every processed by PointNet ensemble compute their corresponding bounding boxes poses. Lastly, stage based on Unscented Kalman...
The rapid development of embedded hardware in autonomous vehicles broadens their computational capabilities, thus bringing the possibility to mount more complete sensor setups able handle driving scenarios higher complexity. As a result, new challenges such as multiple detections same object have be addressed. In this work, siamese network is integrated into pipeline well-known 3D detector approach suppress duplicate proposals coming from different cameras via re-identification....