Shape Carving Methods of Geologic Body Interpretation from Seismic Data Based on Deep Learning
Energies, 2022 The task of seismic data interpretation is a time-consuming and uncertain process. Machine learning tools can help to build a shortcut between raw seismic data and reservoir characteristics of interest. Recently, techniques involving convolutional neural
Sergei Petrov +3 more
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Fully Convolutional Neural Network with Attention Module for Semantic Segmentation [PDF]
Jisuanji kexue yu tansuo, 2022 A fully convolutional neural network is a powerful end-to-end model that is widely used in the field of semantic segmentation and has achieved great success.
OU Yangliu, HE Xi, QU Shaojun
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Fully Convolutional Pyramidal Networks for Semantic Segmentation [PDF]
IEEE Access, 2020 Semantic segmentation networks focus on the scene parsing of an unrestricted open scene. The typical segmentation architectures are stacks consisting of convolutional layers, which are used to extract semantic features. The feature map dimension is sharply changed at sampling units for most of networks, which ensure effective propagation of the ...
Fengxiao Li +8 more
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Segmentation of retinal fluid based on deep learning: application of three-dimensional fully convolutional neural networks in optical coherence tomography images [PDF]
International Journal of Ophthalmology, 2019 AIM: To explore a segmentation algorithm based on deep learning to achieve accurate diagnosis and treatment of patients with retinal fluid. METHODS: A two-dimensional (2D) fully convolutional network for retinal segmentation was employed.
Meng-Xiao Li +6 more
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Fully Convolutional Networks for Handwriting Recognition [PDF]
2018 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 2018 Handwritten text recognition is challenging because of the virtually infinite ways a human can write the same message. Our fully convolutional handwriting model takes in a handwriting sample of unknown length and outputs an arbitrary stream of symbols.
Felipe Petroski Such +4 more
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Instance-Sensitive Fully Convolutional Networks [PDF]
, 2016 Fully convolutional networks (FCNs) have been proven very successful for semantic segmentation, but the FCN outputs are unaware of object instances. In this paper, we develop FCNs that are capable of proposing instance-level segment candidates. In contrast to the previous FCN that generates one score map, our FCN is designed to compute a small set of ...
Jifeng Dai +4 more
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Feasible Architecture for Quantum Fully Convolutional Networks
CoRR, 2021 Fully convolutional networks are robust in performing semantic segmentation, with many applications from signal processing to computer vision. From the fundamental principles of variational quantum algorithms, we propose a feasible pure quantum architecture that can be operated on noisy intermediate-scale quantum devices.
Yusui Chen, Wenhao Hu, Xiang Li
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Fully Convolutional Neural Network with Relation Aware Context Information for Image Parsing
, 2021 Image parsing is among the core tasks in the field of computer vision. The automatic pixel-wise segmentation offers great potential in terms of application adaptability.
Azam, Basim +5 more
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Bone tumor examination based on FCNN-4s and CRF fine segmentation fusion algorithm
Journal of Bone Oncology, 2023 Background and objective: Bone tumor is a kind of harmful orthopedic disease, there are benign and malignant points. Aiming at the problem that the accuracy of the existing machine learning algorithm for bone tumor image segmentation is not high, a bone ...
Shiqiang Wu +6 more
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Distributions of various compositions in granite specimen using fully convolutional network
Zhongguo dizhi zaihai yu fangzhi xuebao, 2021 The distributions of various compositions are the fundamental issues in studying the physical and mechanical properties of rock material. In this study, fully convolutional network (FCN) and the video images photographed during the uniaxial compression ...
Chuxiong ZHU +2 more
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