Results 11 to 20 of about 6,093,681 (207)
Improved Fully Convolutional Network with Conditional Random Fields for Building Extraction
Remote Sensing, 2018 Building extraction from remotely sensed imagery plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications.
Sanjeevan Shrestha, Leonardo Vanneschi
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Proposal-Free Fully Convolutional Network: Object Detection Based on a Box Map
SensorsRegion proposal-based detectors, such as Region-Convolutional Neural Networks (R-CNNs), Fast R-CNNs, Faster R-CNNs, and Region-Based Fully Convolutional Networks (R-FCNs), employ a two-stage process involving region proposal generation followed by ...
Zhihao Su +3 more
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Remote Sensing, 2022 Polarimetric synthetic aperture radar (PolSAR) image classification is a pixel-wise issue, which has become increasingly prevalent in recent years. As a variant of the Convolutional Neural Network (CNN), the Fully Convolutional Network (FCN), which is ...
Wen Xie, Licheng Jiao, Wenqiang Hua
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Investigasi Pengaruh Skema Stride dan Step Training untuk Deteksi Jari Pada Region-based Fully Convolutional Network (R-FCN) dalam Teknologi Augmented Reality [PDF]
Jurnal Ilmiah FIFO, 2021 Abstract Combining the real world with the virtual world and then modeling it in 3D is an effort carried on Augmented Reality (AR) technology. Using fingers for computer operations on multi-devices makes the system more interactive. Marker-based AR is one type of AR that uses markers in its detection.
Hashfi Fadhillah +2 more
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Multi-Head Self-Attention-Based Fully Convolutional Network for RUL Prediction of Turbofan Engines
AlgorithmsRemaining useful life (RUL) prediction is widely applied in prognostic and health management (PHM) of turbofan engines. Although some of the existing deep learning-based models for RUL prediction of turbofan engines have achieved satisfactory results ...
Zhaofeng Liu +4 more
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CAAI Transactions on Intelligence Technology, EarlyView., 2023 Abstract Autonomous vehicles are required to operate in an uncertain environment. Recent advances in computational intelligence techniques make it possible to understand driving scenes in various environments by using a semantic segmentation neural network, which assigns a class label to each pixel.
Yining Hua +4 more
wiley +1 more source
Frontiers in Oncology, 2021 ObjectivesTo automate image delineation of tissues and organs in oncological radiotherapy by combining the deep learning methods of fully convolutional network (FCN) and atrous convolution (AC).MethodsA total of 120 sets of chest CT images of patients ...
Hui Xie +4 more
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FCN+RL: A Fully Convolutional Network followed by Refinement Layers to Offline Handwritten Signature Segmentation [PDF]
2020 International Joint Conference on Neural Networks (IJCNN), 2020 7 pages, 6 figures, Accepted at IJCNN 2020: International Joint Conference on Neural ...
Celso A. M. Lopes Junior +4 more
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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Convolutional neural network (CNN) has achieved remarkable success in polarimetric synthetic aperture radar (PolSAR) image classification. However, the PolSAR image classification is a pixelwise prediction assignment.
Feng Zhao +3 more
doaj +1 more source