Results 71 to 80 of about 5,349,001 (214)

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
doaj   +1 more source

An Optimized Convolutional Neural Network for the 3D Point-Cloud Compression

Sensors, 2023
Due to the tremendous volume taken by the 3D point-cloud models, knowing how to achieve the balance between a high compression ratio, a low distortion rate, and computing cost in point-cloud compression is a significant issue in the field of virtual ...
Guoliang Luo, Bingqin He, Yanbo Xiong, Luqi Wang, Hui Wang, Zhiliang Zhu, Xiangren Shi   +6 more
doaj   +1 more source

Deep solar radiation forecasting with convolutional neural network and long short-term memory network algorithms

, 2019
This paper designs a hybridized deep learning framework that integrates the Convolutional Neural Network for pattern recognition with the Long Short-Term Memory Network for half-hourly global solar radiation (GSR) forecasting.
Deo, Ravinesh C., Ghimire, Sujan, Mi, Jianchun, Raj, Nawin   +3 more
core   +1 more source

A Two-Stream Graph Convolutional Neural Network for Dynamic Traffic Flow Forecasting

, 2020
Forecasting the traffic flow is a critical issue for researchers and practitioners in the field of transportation. Using the graph convolutional network (GCN) is widespread in traffic flow forecasting. Existing GCN-based methods mostly rely on undirected
Zhaoyang Li, Li, Lin, Lin Li, Tao, Xiaohui, Yuquan Peng, Li, Zhaoyang, Peng, Yuquan, Xiaohui Tao   +7 more
core   +1 more source

Cursive Text Recognition in Natural Scene Images Using Deep Convolutional Recurrent Neural Network

, 2022
Text recognition in natural scene images is a challenging problem in computer vision. Different than the optical character recognition (OCR), text recognition in natural scene images is more complex due to variations in text size, colors, fonts ...
Asghar Ali Chandio, MD. Asikuzzaman, Mark R. Pickering, Asikuzzaman, MD., Pickering, Mark R., Leghari, Mehwish, Chandio, Asghar Ali, Mehwish Leghari   +7 more
core   +1 more source

Brain Tumor and Glioma Grade Classification Using Gaussian Convolutional Neural Network [PDF]

, 2022
Understanding brain diseases such as categorizing Brain-Tumor (BT) is critical to assess the tumors and facilitate the patient with proper cure as per their categorizations.
Maryam, S., Baker, T., Rizwan, M., AR Javed, Dhiya, O., Aysha, S.   +5 more
core   +1 more source

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
doaj   +1 more source

Deep Learning Convolutional Neural Network for SARS-CoV-2 Detection Using Chest X-Ray Images

, 2023
The COVID-19 coronavirus illness is caused by a newly discovered species of coronavirus known as SARS-CoV-2. Since COVID-19 has now expanded across many nations, the World Health Organization (WHO) has designated it a pandemic.
Salam Abdulkhaleq Noaman, Ali Mohammed Saleh Ahmed, Inteasar Yaseen Khudhair   +2 more
core   +1 more source

Review of Node Classification Methods Based on Graph Convolutional Neural Networks [PDF]

Jisuanji kexue
Node classification is one of the important research tasks in graph field.In recent years,with the continuous deepening of research on graph convolutional neural network,significant progress has been made in the research and application of node ...
ZHANG Liying, SUN Haihang, SUN Yufa , SHI Bingbo
doaj   +1 more source

Homological Convolutional Neural Networks

CoRR, 2023
Deep learning methods have demonstrated outstanding performances on classification and regression tasks on homogeneous data types (e.g., image, audio, and text data). However, tabular data still pose a challenge, with classic machine learning approaches being often computationally cheaper and equally effective than increasingly complex deep learning ...
Antonio Briola, Yuanrong Wang, Silvia Bartolucci, Tomaso Aste   +3 more
openaire   +3 more sources