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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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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Compressed CNN Plant Leaf Ｒecognition Model Fused with Bayesian
Journal of Harbin University of Science and Technology, 2021 Aiming at the problem that there are many parameters in the process of plant leaf recognition and it is easy to produce over-fitting，in order to reduce the cost of storage and calculation，this paper proposes a plant leaf recognition convolutional ...
YAN Ming, ZHU Liang-kuan, JING Wei-peng
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Distributed Neural Network System for Multimodal Sleep Stage Detection
IEEE Access, 2023 Existing automatic sleep stage detection methods predominantly use convolutional neural network classifiers (CNNs) trained on features extracted from single-modality signals such as electroencephalograms (EEG).
Yi-Hsuan Cheng +2 more
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Image Quality Predictor with Highly Efficient Fully Convolutional Neural Network
Advances in Multimedia, 2022 A highly efficient deep fully convolutional neural network (DFCN) for image quality assessment (IQA) is designed in this paper. The DFCN consists of two branches, one scoring local patches and the other estimating the weights of local patches to enhance ...
Cao Yu-Dong, Liao Xin-Lin, Liu Hai-Yan
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Binary and Multiclass Text Classification by Means of Separable Convolutional Neural Network
Inventions, 2021 In this paper, the structure of a separable convolutional neural network that consists of an embedding layer, separable convolutional layers, convolutional layer and global average pooling is represented for binary and multiclass text classifications ...
Elena Solovyeva, Ali Abdullah
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Klasifikasi Penyakit Mata Menggunakan Convolutional Neural Network (CNN)
Sistemasi: Jurnal Sistem Informasi, 2021 Abstrak Gangguan pada mata atau disebut juga penyakit mata adalah suatu kondisi yang mampu mempengaruhi jangka waktu hidup bagi sebagian orang. Gangguan mata atau penyakit mata banyak sekali jenisnya, diantaranya yaitu katarak, glaukoma dan retina ...
Fani Nurona Cahya +3 more
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Shelf Commodity Identification Method Based on Hybrid Fully Convolutional Automatic Encoder
IEEE Access, 2019 At present, the semantic information segmentation algorithms mainly include FCN (Fully Convolutional Network), PSPNet (Pyramid Scene Parsing Network), Deeplab and so on. In view of the inadequate results of features extracted by these algorithms from RGB
Aofeng Cheng, Guodong Chen, Zheng Wang
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Optimasi Convolutional Neural Network dan K-Fold Cross Validation pada Sistem Klasifikasi Glaukoma
Jurnal Elkomika, 2022 ABSTRAK Pada penelitian ini dilakukan perancangan arsitektur Convolutional Neural Network (CNN) yang terdiri dari 5 layer konvolusi dan 1-fully connected layer untuk mengklasifikasikan citra fundus kedalam kondisi normal, early, moderate, deep, dan ...
YUNENDAH NUR FUADAH +5 more
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Research on Ship Trajectory Classification Based on a Deep Convolutional Neural Network
Journal of Marine Science and Engineering, 2022 With the aim of solving the problems of ship trajectory classification and channel identification, a ship trajectory classification method based on deep a convolutional neural network is proposed.
Tao Guo, Lei Xie
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