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Published in 2022 at "Medical physics"
DOI: 10.1002/mp.15806
Abstract: BACKGROUND Although 4D-CBCT is valuable to provide onboard image guidance for radiotherapy of moving targets, it requires a long acquisition time to achieve sufficient image quality for target localization. To improve the utility, it is…
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Keywords:
deformable convolutional;
quality images;
convolutional networks;
feaco dcn ... See more keywords
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Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3079519
Abstract: Recent researches on image super-resolution (SR) have achieved great progressing with the great development of convolutional neural networks (CNNs). However, existing CNNs usually adopt fixed filter structures and the convolutions just rely on the local…
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Keywords:
image super;
resolution;
scale space;
multi scale ... See more keywords
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Published in 2021 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2020.3042989
Abstract: Capnography, the measurement of the concentration of carbon dioxide in exhaled air has the potential to provide insight into the diagnosis of many cardiopulmonary diseases. Our objective is to develop an effective deep learning algorithm…
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Keywords:
neural network;
deformable convolutional;
quantitative analysis;
convolutional neural ... See more keywords
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Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3086584
Abstract: Recently, deep convolutional neural networks (CNNs) have made important progress in cloud detection with powerful representation learning capability and yield significant performance. However, most existing CNN-based cloud detection methods still face serious challenges because of…
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Keywords:
convolutional cloud;
deformable convolutional;
detection;
detection network ... See more keywords