D object detection based on sparse convolution neural network and feature fusion for autonomous driving in smart cities
Datos Bibliográficos
| ID | 21228362 |
|---|---|
| Autores | Lei Wang (0000-0001-5326-565X, Chinese University of Hong Kong), Xiaoyun Fan (0000-0002-4213-8329, Shenzhen Institutes of Advanced Technology, a), Jiahao Chen (0000-0001-5214-2957, Shenzhen Institutes of Advanced Technology, a), Jun Cheng (0000-0003-0168-1410, Chinese University of Hong Kong, autor de correspondencia), Jun Tan (0000-0002-0288-2487, Sun Yat-sen University), Xiaoliang Ma (0000-0002-0562-4328, Shenzhen University) |
| Año | 2020 |
| Volumen | 54 |
| Páginas | 102002 |
| Fecha de publicación | 2020-03-01 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Sustainable Cities and Society (JOURNAL) |
| Identificadores de la revista | ISSN: 2210-6707 • E-ISSN: 2210-6715 |
| Editorial | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.scs.2019.102002 |
| OpenAlex | W2997495697 |
| Idioma | EN |
| Citas recibidas | 6 |
| Referencias citadas | 21 |
Artificial neural network · Computer vision · Feature extraction · Object detection · Pedestrian · Pedestrian detection · Point cloud · Voxel · Advanced Neural Network Applications · Autonomous Vehicle Technology and Safety · Computer Science · Engineering · Video Surveillance and Tracking Methods · Artificial Intelligence
Evaluating the performances of several artificial intelligence methods in forecasting daily streamflow time series for sustainable water resources management
Deep metric learning for image retrieval in smart city development
Integrating computer vision and traffic modeling for near-real-time signal timing optimization of multiple intersections
Cascade saccade machine learning network with hierarchical classes for traffic sign detection
Assessing the impacts of connected-and-autonomous vehicle management strategy on the environmental sustainability of urban expressway system
Automated and disrupted mobilities
| Obras citantes distintas | 6 |
|---|---|
| Citas por año | 1,2 |
| Intervalo de citas | 2021 - 2025 (5) |
| Velocidad de citación | recent |
| Altamente citado | No |
| Tipos de cita | Neutras: 6 |