|
|
|
|
|
Ariadna Calcines Rosario, Frederic Auchère, Alain Jody Corso, Giulio Del Zanna, Jaroslav Dudík, Samuel Gissot, Laura A. Hayes, Graham S. Kerr, Christian Kintziger, Sarah A. Matthews, Sophie Musset, David Orozco Suárez, Vanessa Polito, Hamish A. S. Reid and Daniel F. Ryan
Particle acceleration, and the thermalisation of energetic particles, are fundamental processes across the universe. Whilst the Sun is an excellent object to study this phenomenon, since it is the most energetic particle accelerator in the Solar System, ...
ver más
|
|
|
|
|
|
|
|
|
Xinmin Li, Yingkun Wei, Jiahui Li, Wenwen Duan, Xiaoqiang Zhang and Yi Huang
Object detection in unmanned aerial vehicle (UAV) images has become a popular research topic in recent years. However, UAV images are captured from high altitudes with a large proportion of small objects and dense object regions, posing a significant cha...
ver más
|
|
|
|
|
|
|
|
|
Fatima Zahra Guerrouj, Sergio Rodríguez Flórez, Mohamed Abouzahir, Abdelhafid El Ouardi and Mustapha Ramzi
Convolutional Neural Networks (CNNs) have been incredibly effective for object detection tasks. YOLOv4 is a state-of-the-art object detection algorithm designed for embedded systems. It is based on YOLOv3 and has improved accuracy, speed, and robustness....
ver más
|
|
|
|
|
|
|
|
|
Ziyi Li, Yang Li, Yanping Wang, Guangda Xie, Hongquan Qu and Zhuoyang Lyu
With the rapid development of deep learning, more and more complex models are applied to 3D point cloud object detection to improve accuracy. In general, the more complex the model, the better the performance and the greater the computational resource co...
ver más
|
|
|
|
|
|
|
|
|
Rio Arifando, Shinji Eto and Chikamune Wada
Object detection is crucial for individuals with visual impairment, especially when waiting for a bus. In this study, we propose a lightweight and highly accurate bus detection model based on an improved version of the YOLOv5 model. We propose integratin...
ver más
|
|
|
|