Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Ying Li"'
Publikováno v:
Remote Sensing, Vol 13, Iss 1440, p 1440 (2021)
Remote Sensing; Volume 13; Issue 8; Pages: 1440
Remote Sensing; Volume 13; Issue 8; Pages: 1440
Accurate change detection in optical aerial images by using deep learning techniques has been attracting lots of research efforts in recent years. Correct change-detection results usually involve both global and local deep learning features. Existing
Autor:
Yanning Zhang, Yunpeng Bai, Ying Li, Juanni Liu, Huyan Lang, Quan Zhou, Cui Tao, Dongmei Jiang, Yi Zhang, Jiayuan Wei
Publikováno v:
Remote Sensing
Volume 13
Issue 4
Pages: 683
Remote Sensing, Vol 13, Iss 683, p 683 (2021)
Volume 13
Issue 4
Pages: 683
Remote Sensing, Vol 13, Iss 683, p 683 (2021)
Onboard real-time object detection in remote sensing images is a crucial but challenging task in this computation-constrained scenario. This task not only requires the algorithm to yield excellent performance but also requests limited time and space
Global Cyclone and Anticyclone Detection Model Based on Remotely Sensed Wind Field and Deep Learning
Publikováno v:
Remote Sensing, Vol 12, Iss 3111, p 3111 (2020)
Cyclone detection is a classical topic and researchers have developed various methods of cyclone detection based on sea-level pressure, cloud image, wind field, etc. In this article, a deep-learning algorithm is incorporated with modern remote-sensin
Publikováno v:
Remote Sensing
Volume 12
Issue 17
Pages: 2717
Remote Sensing, Vol 12, Iss 2717, p 2717 (2020)
Volume 12
Issue 17
Pages: 2717
Remote Sensing, Vol 12, Iss 2717, p 2717 (2020)
The Global Navigation Satellite System (GNSS) Radio Occultation (RO) retrieved temperature and specific humidity profiles can be widely used for weather and climate studies in troposphere. However, some aspects, such as the influences of background d
Publikováno v:
Remote Sensing, Vol 12, Iss 2116, p 2116 (2020)
Remote Sensing
Volume 12
Issue 13
Pages: 2116
Remote Sensing
Volume 12
Issue 13
Pages: 2116
Fengyun-3C (FY-3C) is the first Chinese satellite that is capable of using the Radio Occultation (RO) technique to retrieve atmospheric profiles. This research evaluates the quality of FY-3C RO profiles including refractivity, temperature, and specif
Publikováno v:
Remote Sensing, Vol 11, Iss 22, p 2608 (2019)
Remote Sensing
Volume 11
Issue 22
Pages: 2608
Remote Sensing
Volume 11
Issue 22
Pages: 2608
In recent years, convolutional neural networks (CNNs) have shown promising performance in the field of multispectral (MS) and panchromatic (PAN) image fusion (MS pansharpening). However, the small-scale data and the gradient vanishing problem have be
Publikováno v:
Remote Sensing, Vol 13, Iss 1607, p 1607 (2021)
Remote Sensing; Volume 13; Issue 9; Pages: 1607
Remote Sensing; Volume 13; Issue 9; Pages: 1607
Marine oil spill detection is vital for strengthening the emergency commands of oil spill accidents and repairing the marine environment after a disaster. Polarimetric Synthetic Aperture Radar (Pol-SAR) can obtain abundant information of the targets
Publikováno v:
Remote Sensing, Vol 13, Iss 1070, p 1070 (2021)
Mapping new and old buildings are of great significance for understanding socio-economic development in rural areas. In recent years, deep neural networks have achieved remarkable building segmentation results in high-resolution remote sensing images
Publikováno v:
Remote Sensing, Vol 11, Iss 7, p 793 (2019)
Remote Sensing; Volume 11; Issue 7; Pages: 793
Remote Sensing; Volume 11; Issue 7; Pages: 793
The purpose of this study is to obtain oil tank volumes from high-resolution satellite imagery to meet the need to measure oil tank volume globally. A preprocessed remote sensing HSV image is used to extract the shadow of the oil tank by Otsu thresho
Publikováno v:
Remote Sensing, Vol 10, Iss 10, p 1644 (2018)
Remote Sensing
Volume 10
Issue 10
Pages: 1644
Remote Sensing
Volume 10
Issue 10
Pages: 1644
Following the growing availability of low-cost, commercially available unmanned aerial vehicles (UAVs), more and more research efforts have been focusing on object tracking using videos recorded from UAVs. However, tracking from UAV videos poses many