Results 31 to 40 of about 12,912,851 (287)

MapGlue: Multimodal Remote Sensing Image Matching

CoRR
The dataset and code are available at https://github.com/PeihaoWu ...
Peihao Wu, Yongxiang Yao, Wenfei Zhang, Dong Wei, Yi Wan 0001, Yansheng Li 0001, Yongjun Zhang 0002   +6 more
openaire   +4 more sources

Multimodal 3D photoacoustic remote sensing and confocal fluorescence microscopy imaging [PDF]

Journal of Biomedical Optics, 2021
Complementary absorption and fluorescence contrast could prove useful for a wide range of biomedical applications. However, current absorption-based photoacoustic microscopy systems require the ultrasound transducers to physically touch the samples, thereby increasing contamination and limiting strong optical focusing in reflection mode.We sought to ...
Restall, Brendon S., Kedarisetti, Pradyumna, Haven, Nathaniel J. M., Martell, Matthew T., Zemp, Roger J.   +4 more
openaire   +2 more sources

YOLOrs: Object Detection in Multimodal Remote Sensing Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Deep-learning object detection methods that are designed for computer vision applications tend to underperform when applied to remote sensing data. This is because contrary to computer vision, in remote sensing, training data are harder to collect and ...
Manish Sharma, Mayur Dhanaraj, Srivallabha Karnam, Dimitris G. Chachlakis, Raymond Ptucha, Panos P. Markopoulos, Eli Saber   +6 more
doaj   +1 more source

Robust Registration of Multimodal Remote Sensing Images Based on Structural Similarity [PDF]

IEEE Transactions on Geoscience and Remote Sensing, 2017
Automatic registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR) is a challenging task due to the significant non-linear radiometric differences between these data. To address this problem, this paper proposes a novel feature descriptor named the Histogram of Orientated Phase Congruency (HOPC), which is based on the structural ...
Yuanxin Ye, Jie Shan, Lorenzo Bruzzone, Li Shen 0004   +3 more
openaire   +4 more sources

MRSSC: A BENCHMARK DATASET FOR MULTIMODAL REMOTE SENSING SCENE CLASSIFICATION [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2021
Scene classification based on multi-source remote sensing image is important for image interpretation, and has many applications, such as change detection, visual navigation and image retrieval. Deep learning has become a research hotspot in the field of
K. Liu, A. Wu, A. Wu, X. Wan, S. Li, S. Li   +5 more
doaj   +1 more source

Remote Sensing Image Haze Removal Based on Superpixel

, 2023
The presence of haze significantly degrades the quality of remote sensing images, resulting in issues such as color distortion, reduced contrast, loss of texture, and blurred image edges, which can ultimately lead to the failure of remote sensing ...
Tiecheng Bai, Yufeng He, Cuili Li
core   +1 more source

A Deep Semantic Alignment Network for the Cross-Modal Image-Text Retrieval in Remote Sensing

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Because of the rapid growth of multimodal data from the internet and social media, a cross-modal retrieval has become an important and valuable task in recent years.The purpose of the cross-modal retrieval is to obtain the result data in one modality (e ...
Qimin Cheng, Yuzhuo Zhou, Peng Fu, Yuan Xu, Liang Zhang   +4 more
doaj   +1 more source

A review of parallel computing for large-scale remote sensing image mosaicking [PDF]

, 2015
Interest in image mosaicking has been spurred by a wide variety of research and management needs. However, for large-scale applications, remote sensing image mosaicking usually requires significant computational capabilities.
Wei, Jingbo, He, Jijun, Chen, Lajiao, Liu, Peng, Jie, Wei, Ma, Yan   +5 more
core   +1 more source

A Method for Multimodal Remote Sensing Image Classification

Journal of Organizational and End User Computing
In remote sensing, images are widely used in applications, such as land cover classification, urban monitoring, and disaster management, providing rich information about the Earth's surface. However, due to data heterogeneity and scarcity, different modalities of remote-sensing images often face challenges in classification tasks.
Zhanming Sun, Bin Hu
openaire   +1 more source

Multimodal Contrastive Learning for Remote Sensing Image Feature Extraction Based on Relaxed Positive Samples

Sensors
Traditional multimodal contrastive learning brings text and its corresponding image closer together as a positive pair, where the text typically consists of fixed sentence structures or specific descriptive statements, and the image features are ...
Zhenshi Zhang, Qiujun Li, Wenxuan Jing, Guangjun He, Lili Zhu, Shijuan Gao   +5 more
doaj   +1 more source