Results 61 to 70 of about 300,366 (322)

SAR Target Detection Based on Domain Adaptive Faster R-CNN with Small Training Data Size

Remote Sensing, 2021
It is expensive and time-consuming to obtain a large number of labeled synthetic aperture radar (SAR) images. In the task of small training data size, the results of target detection on SAR images using deep network approaches are usually not ideal.
Yuchen Guo, Lan Du, Guoxin Lyu
doaj   +1 more source

Optical Remote Sensing Image Denoising and Super-Resolution Reconstructing Using Optimized Generative Network in Wavelet Transform Domain

Remote Sensing, 2021
High spatial quality (HQ) optical remote sensing images are very useful for target detection, target recognition and image classification. Due to the influence of imaging equipment accuracy and atmospheric environment, HQ images are difficult to acquire,
Xubin Feng, Wuxia Zhang, Xiuqin Su, Zhengpu Xu   +3 more
doaj   +1 more source

Ship Detection with Deep Learning in Optical Remote-Sensing Images: A Survey of Challenges and Advances

Remote Sensing
Ship detection aims to automatically identify whether there are ships in the images, precisely classifies and localizes them. Regardless of whether utilizing early manually designed methods or deep learning technology, ship detection is dedicated to ...
Tianqi Zhao, Yongcheng Wang, Zheng Li, Yunxiao Gao, Chi Chen, Hao Feng, Zhikang Zhao   +6 more
semanticscholar   +1 more source

Cooperative Detection of Ships in Optical and SAR Remote Sensing Images Based on Neighborhood Saliency

Leida xuebao
In ship detection through remote sensing images, optical images often provide rich details and texture information; however, the quality of such optical images can be affected by cloud and fog interferences.
Qiang ZHANG, Zhihao WANG, Xueqian WANG, Gang LI, Liwei HUANG, Huina SONG, Zhaohui SONG   +6 more
doaj   +1 more source

Remote Sensing Image Denoising Based on Deep and Shallow Feature Fusion and Attention Mechanism

Remote Sensing, 2022
Optical remote sensing images are widely used in the fields of feature recognition, scene semantic segmentation, and others. However, the quality of remote sensing images is degraded due to the influence of various noises, which seriously affects the ...
Lintao Han, Yuchen Zhao, Hengyi Lv, Yisa Zhang, Hailong Liu, Guoling Bi   +5 more
doaj   +1 more source

Conv-trans dual network for landslide detection of multi-channel optical remote sensing images

Frontiers in Earth Science, 2023
Landslide detection is crucial for disaster management and prevention. With the advent of multi-channel optical remote sensing technology, detecting landslides have become more accessible and more accurate.
Xin Chen, Mingzhe Liu, Dongfen Li, Jiaru Jia, Aiqing Yang, Wenfeng Zheng, Lirong Yin   +6 more
semanticscholar   +1 more source

Prediction of Myasthenia Gravis Worsening: A Machine Learning Algorithm Using Wearables and Patient‐Reported Measures

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Background Myasthenia gravis (MG) is a rare disorder characterized by fluctuating muscle weakness with potential life‐threatening crises. Timely interventions may be delayed by limited access to care and fragmented documentation. Our objective was to develop predictive algorithms for MG deterioration using multimodal telemedicine data ...
Maike Stein, Haoqi Sun, Sophie Lehnerer, Lea Gerischer, Maximilian Mönch, Christian Meisel, Andreas Meisel, Pushpa Narayanaswami   +7 more
wiley   +1 more source

Discrete-Time Noise-Suppression Neural Dynamics for Optical Remote Sensing Image Extraction

IEEE Access, 2023
Optical remote sensing is an important method of observing objects over large areas. Naturally, it is essential to extract the target from optical remote sensing images.
Yizhen Xiong, Difeng Wang, Dongyang Fu, Yan Wang   +3 more
doaj   +1 more source

Evaluation of Landsat-8 and Sentinel-2A Aerosol Optical Depth Retrievals Across Chinese Cities and Implications for Medium Spatial Resolution Urban Aerosol Monitoring [PDF]

, 2019
In urban environments, aerosol distributions may change rapidly due to building and transport infrastructure and human population density variations.
Huang, Haiyan, Li, Zhongbin, Roy, David P., Vermote, Eric, Zhang, Hankui   +4 more
core   +2 more sources

Adaptive Dual-Stream Sparse Transformer Network for Salient Object Detection in Optical Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Excellent performance has been demonstrated by convolutional neural network (CNN) in salient object detection for optical remote sensing images (ORSI-SOD).
Jie Zhao, Yun Jia, Lin Ma, Lidan Yu
semanticscholar   +1 more source