Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Xiangyu Zhuo"'
Publikováno v:
Meitan xuebao, Vol 49, Iss S1, Pp 404-412 (2024)
The Zhundong region in Xinjiang has abundant high-Na coal resource, which can be used as high-quality fuel and chemical raw material. However, the high-Na content can lead to severe equipment pollution and ash slagging during combustion and gasificat
Externí odkaz:
https://doaj.org/article/bbb8d3002c254355b904320abf038a7d
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 431-448 (2023)
Detection and vectorization of windows from building façades are important for building energy modeling, civil engineering, and architecture design. However, current applications still face the challenges of low accuracy and lack of automation. In t
Externí odkaz:
https://doaj.org/article/18d6fe5c9b32435eb78837590fb74e4f
Publikováno v:
Remote Sensing, Vol 11, Iss 2, p 145 (2019)
The tremendous advances in deep neural networks have demonstrated the superiority of deep learning techniques for applications such as object recognition or image classification. Nevertheless, deep learning-based methods usually require a large amoun
Externí odkaz:
https://doaj.org/article/65519b40450b411bb56c4363ad21d018
Publikováno v:
Remote Sensing, Vol 9, Iss 4, p 376 (2017)
Recent years have witnessed the fast development of UAVs (unmanned aerial vehicles). As an alternative to traditional image acquisition methods, UAVs bridge the gap between terrestrial and airborne photogrammetry and enable flexible acquisition of hi
Externí odkaz:
https://doaj.org/article/8db700f07efa4a95b4e19b31f4594645
Autor:
Jiaojiao Tian, Peter Reinartz, Ksenia Bittner, Thomas Krauss, Miguel Pato, Raquel de los Reyes, Xiangyu Zhuo, Pablo d'Angelo, Seyed Majid Azimi, Stefan Auer, Daniele Cerra, Nina Merkle
Publikováno v:
IGARSS
This paper describes the winning contribution to the 2019 IEEE GRSS Data Fusion Contest Multi-view Semantic Stereo Challenge. In this challenge, a digital surface model(DSM) and a semantic segmentation should be derived from a large number of multi-s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d58717ac93fa3a85b901bc72d9b3fc9d
https://elib.dlr.de/130254/
https://elib.dlr.de/130254/
Publikováno v:
Milena Mönks
JURSE
JURSE
Building semantic segmentation is a crucial task for building information modeling (BIM). Current research generally exploits terrestrial image data, which provides only limited view of a building. By contrast, oblique imagery acquired by unmanned ae
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b52408dae7cd03557130d1d62fe2c7f1
https://elib.dlr.de/129075/
https://elib.dlr.de/129075/
Publikováno v:
IGARSS
Significantly outperforming traditional machine learning methods, deep convolutional neural networks have gained increasing popularity in the application of image classification and segmentation. Nevertheless, deep learning-based methods usually requ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2efbe9085e19ec7411aa28fc414637d
https://elib.dlr.de/123995/
https://elib.dlr.de/123995/
Publikováno v:
Remote Sensing; Volume 10; Issue 4; Pages: 624
Building footprint information is vital for 3D building modeling. Traditionally, in remote sensing, building footprints are extracted and delineated from aerial imagery and/or LiDAR point cloud. Taking a different approach, this paper is dedicated to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=multidiscipl::4fd98d71cbec64cf456e7522fc11f721
Publikováno v:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XL-1-W4, Pp 201-206 (2015)
Manned aircraft has long been used for capturing large-scale aerial images, yet the high costs and weather dependence restrict its availability in emergency situations. In recent years, MAV (Micro Aerial Vehicle) emerged as a novel modality for aeria
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8aac0ab54d3435878aba87359be93c7
https://doi.org/10.5194/isprsarchives-xl-1-w4-201-2015
https://doi.org/10.5194/isprsarchives-xl-1-w4-201-2015
Publikováno v:
Remote Sensing; Volume 9; Issue 4; Pages: 376
Remote Sensing, Vol 9, Iss 4, p 376 (2017)
Remote Sensing, Vol 9, Iss 4, p 376 (2017)
Recent years have witnessed the fast development of UAVs (unmanned aerial vehicles). As an alternative to traditional image acquisition methods, UAVs bridge the gap between terrestrial and airborne photogrammetry and enable flexible acquisition of hi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddea52c4c6838454b982ef5586bd7bce