Transformer and CNN Hybrid Deep Neural Network for Semantic Segmentation of Very-high-resolution Remote Sensing Imagery
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3144894
Abstract: This paper presents a transformer and CNN hybrid deep neural network for semantic segmentation of very-high-resolution remote sensing imagery. The model follows an encoder-decoder structure. The encoder module uses a new universal backbone swin transformer… read more here.
Keywords: network; cnn hybrid; remote sensing; transformer cnn ... See more keywords
CNN-KA: A Hybrid P-Phase Picking Method for Microseismic Source Location in Deep Mine With Complex Geological Conditions
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DOI: 10.1109/tgrs.2025.3528433
Abstract: Microseismic (MS) technology is one of the effective methods for engineering fracture monitoring and has been widely used in coal mining. The accurate P-phase arrivals are critical for improving the accuracy of source locations and… read more here.
Keywords: cnn; cnn hybrid; coal; source ... See more keywords
Diabetic Retinopathy Classification Using CNN and Hybrid Deep Convolutional Neural Networks
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DOI: 10.3390/sym14091932
Abstract: Diabetic Retinopathy (DR) is an eye condition that mainly affects individuals who have diabetes and is one of the important causes of blindness in adults. As the infection progresses, it may lead to permanent loss… read more here.
Keywords: cnn hybrid; cnn densenet; classification; hybrid cnn ... See more keywords