Results 41 to 50 of about 1,087,010 (389)

NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark [PDF]

arXiv.org, 2023
Vision-centric Bird's-Eye View (BEV) representation is essential for autonomous driving systems (ADS). Multi-frame temporal fusion which leverages historical information has been demonstrated to provide more comprehensive perception results.
Xi Zhu, Xiya Cao, Zhiwei Dong, Caifa Zhou, Qiangbo Liu, W. Li, Yongliang Wang   +6 more
semanticscholar   +1 more source

Comparison of Five Spatio-Temporal Satellite Image Fusion Models over Landscapes with Various Spatial Heterogeneity and Temporal Variation [PDF]

, 2019
In recent years, many spatial and temporal satellite image fusion (STIF) methods have been developed to solve the problems of trade-off between spatial and temporal resolution of satellite sensors.
Chen, Xiuwan, Im, Jungho, Ke, Yinghai, Liu, Maolin, Yin, Qi   +4 more
core   +1 more source

Spatiotemporal Calibration of 3D Millimetre-Wavelength Radar-Camera Pairs [PDF]

IEEE Transactions on Robotics (T-RO), Vol. 39, No. 6, pp. 4552-4566, Dec. 2023, 2022
Autonomous vehicles (AVs) fuse data from multiple sensors and sensing modalities to impart a measure of robustness when operating in adverse conditions. Radars and cameras are popular choices for use in sensor fusion; although radar measurements are sparse in comparison to camera images, radar scans penetrate fog, rain, and snow.
arxiv   +1 more source

A Novel Deep Learning-Based Spatiotemporal Fusion Method for Combining Satellite Images with Different Resolutions Using a Two-Stream Convolutional Neural Network

Remote Sensing, 2020
Spatiotemporal fusion is considered a feasible and cost-effective way to solve the trade-off between the spatial and temporal resolution of satellite sensors.
Duo Jia, Changqing Song, Changxiu Cheng, Shi Shen, Lixin Ning, Chun Hui   +5 more
doaj   +1 more source

Feasibility of the Spatiotemporal Fusion Model in Monitoring Ebinur Lake’s Suspended Particulate Matter under the Missing-Data Scenario

Remote Sensing, 2021
High-frequency monitoring of suspended particulate matter (SPM) concentration can improve water resource management. Missing high-resolution satellite images could hamper remote-sensing SPM monitoring.
Changjiang Liu, Pan Duan, Fei Zhang, Chi-Yung Jim, Mou Leong Tan, Ngai Weng Chan   +5 more
doaj   +1 more source

Tree Species Classification over Cloudy Mountainous Regions by Spatiotemporal Fusion and Ensemble Classifier

Forests, 2023
Accurate mapping of tree species is critical for the sustainable development of the forestry industry. However, the lack of cloud-free optical images makes it challenging to map tree species accurately in cloudy mountainous regions.
Liang Cui, Shengbo Chen, Yongling Mu, Xitong Xu, Bin Zhang, Xiuying Zhao   +5 more
semanticscholar   +1 more source

Stability Analysis of Unmixing-Based Spatiotemporal Fusion Model: A Case of Land Surface Temperature Product Downscaling

Remote Sensing, 2023
The unmixing-based spatiotemporal fusion model is one of the effective ways to solve limitations in temporal and spatial resolution tradeoffs in a single satellite sensor.
Min Li, Shanxin Guo, Jinsong Chen, Yuguang Chang, Luyi Sun, Longlong Zhao, Xiaoli Li, H. Yao   +7 more
semanticscholar   +1 more source

A modified flexible spatiotemporal data fusion model

Frontiers of Earth Science, 2020
Remote sensing spatiotemporal fusion models blend multi-source images of different spatial resolutions to create synthetic images with high resolution and frequency, contributing to time series research where high quality observations are not available with sufficient frequency.
Yue Zeng, Xingrong Li, Jia Tang, Qing Zhang, Jingyu Zeng, Rongrong Zhang, Qianfeng Wang, Qianfeng Wang, Li Zhang, Jie Zou, Zhanghua Xu, Jinghan Li   +11 more
openaire   +2 more sources

Digital Soil Mapping Based on Fine Temporal Resolution Landsat Data Produced by Spatiotemporal Fusion

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
Multitemporal Landsat-8 satellite images with fine spatial resolution (i.e., 30 m) are crucial for modern digital soil mapping (DSM). Generally, cloud-free images covering bare topsoil are common choices for DSM.
Haoxuan Yang, Qunming Wang, Xiaofeng Ma, Wenqi Liu, Huanjun Liu   +4 more
semanticscholar   +1 more source

Machine-learning-estimation of high-spatiotemporal-resolution chlorophyll-a concentration using multi-satellite imagery

Sustainable Environment Research, 2023
Chlorophyll-a concentration for quantifying phytoplankton biomass is commonly used as an indicator for evaluating the trophic level of lakes and water quality.
Wachidatin Nisaul Chusnah, Hone-Jay Chu, Tatas, Lalu Muhamad Jaelani   +3 more
doaj   +1 more source