Results 61 to 70 of about 2,004,297 (387)
Algorithms, 2018 Variation in the format and classification requirements for remote sensing data makes establishing a standard remote sensing sample dataset difficult. As a result, few remote sensing deep neural network models have been widely accepted.
Wei Cui, Qi Zhou, Zhendong Zheng
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Interpretable Convolutional Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 This paper proposes a method to modify traditional convolutional neural networks (CNNs) into interpretable CNNs, in order to clarify knowledge representations in high conv-layers of CNNs. In an interpretable CNN, each filter in a high conv-layer represents a certain object part.
Ying Nian Wu +2 more
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IEEE Access, 2022 Skin cancer is caused due to unusual development of skin cells and deadly type cancer. Early diagnosis is very significant and can avoid some categories of skin cancers, such as melanoma and focal cell carcinoma. The recognition and the classification of
A. Sharma +9 more
semanticscholar +1 more source
IEEE Access, 2020 In this paper, ultrasound imaging of benign and malignant thyroid nodules to predict the depth of the learning algorithm, built on circulation volume product thyroid ultrasound image neural network forecasting model.
Yinghui Lu, Yi Yang, Wan Chen
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Orthogonal Features Extraction Method and Its Application in Convolution Neural Network
Shanghai Jiaotong Daxue xuebao, 2021 In view of feature redundancy in the convolutional neural network, the concept of orthogonal vectors is introduced into features. Then, a method for orthogonal features extraction of convolutional neural network is proposed from the perspective of ...
LI Chen, LI Jianxun
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Graph Convolutional Neural Networks for Web-Scale Recommender Systems [PDF]
Knowledge Discovery and Data Mining, 2018 Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. However, making these methods practical and scalable to web-scale recommendation tasks with billions of items
Rex Ying +5 more
semanticscholar +1 more source
INVESTIGATIONS ON THE POTENTIAL OF CONVOLUTIONAL NEURAL NETWORKS FOR VEHICLE CLASSIFICATION BASED ON RGB AND LIDAR DATA [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017 In recent years, there has been a significant improvement in the detection, identification and classification of objects and images using Convolutional Neural Networks.
R. Niessner, H. Schilling, B. Jutzi
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Toward Understanding Convolutional Neural Networks from Volterra Convolution Perspective [PDF]
arXiv, 2021 We make an attempt to understanding convolutional neural network by exploring the relationship between (deep) convolutional neural networks and Volterra convolutions. We propose a novel approach to explain and study the overall characteristics of neural networks without being disturbed by the horribly complex architectures.
arxiv
Research on road extraction of remote sensing image based on convolutional neural network
EURASIP Journal on Image and Video Processing, 2019 Road is an important kind of basic geographic information. Road information extraction plays an important role in traffic management, urban planning, automatic vehicle navigation, and emergency management.
Yuantao Jiang
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A graph neural network-enhanced knowledge graph framework for intelligent analysis of policing cases
Mathematical Biosciences and Engineering, 2023 In this paper, we model a knowledge graph based on graph neural networks, conduct an in-depth study on building knowledge graph embeddings for policing cases, and design a graph neural network-enhanced knowledge graph framework.
Hongqiang Zhu
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