Results 31 to 40 of about 2,071 (151)
2PN: A Unified Panoptic Segmentation Network with Attention Module
Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022 Comprehensive and accurate surveillance of the environment forms the basis of secure Internet of things (IoTs), the threats can be observed, and the AI services of IoT systems can be preserved. Panoptic segmentation is an efficient and popular approach for environmental surveillance based on images captured by smart sensing devices.
Jianwen Wang, Zhiqin Liu, Yan Huo
wiley +1 more source
QUALITY ASPECTS OF HIGH-DEFINITION MAPS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021 A self-driving vehicle is one of the most expected inventions in the near future. These vehicles are enabled by several technological developments, like artificial intelligence, robust control, vehicular sensors, and high-speed communication.
J. M. Lógó +3 more
doaj +1 more source
A Deep Learning‐Based Semantic Segmentation Architecture for Autonomous Driving Applications
Wireless Communications and Mobile Computing, Volume 2022, Issue 1, 2022., 2022 In recent years, the development of smart transportation has accelerated research on semantic segmentation as it is one of the most important problems in this area. A large receptive field has always been the center of focus when designing convolutional neural networks for semantic segmentation.
Sharjeel Masood +8 more
wiley +1 more source
Learning a Robust Hybrid Descriptor for Robot Visual Localization
Journal of Robotics, Volume 2022, Issue 1, 2022., 2022 Long‐term robust visual localization is one of the main challenges of long‐term visual navigation for mobile robots. Due to factors such as illumination, weather, and season, mobile robots continuously navigate with visual information in a complex scene, which is likely to lead to failure localization within a few hours.
Qingwu Shi +4 more
wiley +1 more source
Volare alto con l'Intelligenza Artificiale
GEOmedia, 2021 JOHN MCCARTHY, computer scientist at Stanford University, first coined the term "artificial intelligence” in 1955, defining it as, "the science and engineering of making intelligent machines, especially intelligent computer programs.” Machines are ...
Marc M. Delgado
doaj +1 more source
Toward explainable and advisable model for self‐driving cars
Applied AI Letters, Volume 2, Issue 4, December 2021., 2021 Towards learning more human‐like driving behavior, we propose to use human advice in the form of observation‐action rules. Abstract Humans learn to drive through both practice and theory, for example, by studying the rules, while most self‐driving systems are limited to the former.
Jinkyu Kim +7 more
wiley +1 more source
Crowdsourced Street-Level Imagery as a Potential Source of In-Situ Data for Crop Monitoring
Land, 2018 New approaches to collect in-situ data are needed to complement the high spatial (10 m) and temporal (5 d) resolution of Copernicus Sentinel satellite observations.
Raphaël d’Andrimont +5 more
doaj +1 more source
IET Intelligent Transport Systems, Volume 15, Issue 4, Page 483-503, April 2021., 2021 Abstract This paper presents an efficient and layout‐independent Automatic License Plate Recognition (ALPR) system based on the state‐of‐the‐art you only look once (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.
Rayson Laroca +5 more
wiley +1 more source
Volunteered and crowdsourced geographic information: the OpenStreetMap project
Journal of Spatial Information Science, 2020 Advancements in technology over the last two decades have changed how spatial data are created and used. In particular, in the last decade, volunteered geographic information (VGI), i.e., the crowdsourcing of geographic information, has revolutionized ...
Michela Bertolotto +2 more
doaj +1 more source
AntMapper-based workflow for the crowdsourced Mapillary data preprocessing
, 2022 Mapillary imagery is a novel crowdsourced data offering street-level imagery and GPS trajectory data simultaneously. Image inconsistency and measurement error of GPS trajectory data are two main issues obstacle Mapillary data applications in urban studies. In this paper, proposed workflow of crowdsourced Mapillary data cleaned random images and matched
Wang, Meihui, Haworth, James
openaire +2 more sources