Results 71 to 80 of about 42,190 (170)

Extraction of Retinal Layers Through Convolution Neural Network (CNN) in an OCT Image for Glaucoma Diagnosis. [PDF]

J Digit Imaging, 2020
Raja H, Akram MU, Shaukat A, Khan SA, Alghamdi N, Khawaja SG, Nazir N.   +6 more
europepmc   +1 more source

Application of Spatio-Temporal Context and Convolution Neural Network (CNN) in Grooming Behavior of Bactrocera minax (Diptera: Trypetidae) Detection and Statistics. [PDF]

Insects, 2020
Zhang Z, Zhan W, He Z, Zou Y.
europepmc   +1 more source

Deep Learning and Convolutional Neural Networks (CNNs)

Deep Learning (DL), a subfield of Artificial Intelligence (AI) and Machine Learning (ML), has revolutionized computational intelligence by enabling machines to automatically learn hierarchical representations from large datasets. Among the various deep learning architectures, Convolutional Neural Networks have emerged as a dominant framework ...
V. V. Virginia, U.M. Mbanaso, E.S. Chaku, I.O. Clementina, Gilbert Aimufua   +4 more
openaire   +1 more source

Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model

BMC Public Health
Background Influenza, an acute infectious respiratory disease, presents a significant global health challenge. Accurate prediction of influenza activity is crucial for reducing its impact.
Guofan Li, Yan Li, Guangyue Han, Caixiao Jiang, Minghao Geng, Nana Guo, Wentao Wu, Shangze Liu, Zhihuai Xing, Xu Han, Qi Li   +10 more
doaj   +1 more source

RIC-CNN: Rotation-Invariant Coordinate Convolutional Neural Network

Pattern Recognition
In recent years, convolutional neural network has shown good performance in many image processing and computer vision tasks. However, a standard CNN model is not invariant to image rotations. In fact, even slight rotation of an input image will seriously degrade its performance.
Zhao Guoying, Mo Hanlin
openaire   +2 more sources

Lightweight monocular depth estimation using a fusion-improved transformer

Scientific Reports
The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transformers as the ...
Xin Sui, Song Gao, Aigong Xu, Cong Zhang, Changqiang Wang, Zhengxu Shi   +5 more
doaj   +1 more source

Short Text Feature Extraction and Classification Based on Serial–Parallel Convolutional Gated Recurrent Neural Network

工程科学与技术, 2019
In order to address the problems that the features and information is limited in short text, the short text features are not fully expressed by traditional convolutional neural network (CNN) and recurrent neural network (RNN), a text classification model
Xianlun TANG, Wenxing LIN, Yiming DU, Ting WANG   +3 more
doaj  

Research on Detection of Bird Nests in Overhead Catenary Based on Deep Convolutional Neural Network

机车电传动, 2019
Nesting on railway catenaries by birds has been an important cause of catenary failure. At present, the inspection for judging the existence of bird’s nests is carried out artificially, which has much shortcomings in heavy working intensity, high missing-
Deqiang HE, Zhou JIANG, Jiyong CHEN, Yanjie YANG, Xiaoyang YAO   +4 more
doaj  

Convolutional neural network(CNN)モデル

Farumashia, 2018
OHNO, Ken, MATSUMOTO, Kentaro
openaire   +1 more source

Estimation of battery SOC using a combined approach of temporal convolutional networks and Unscented Kalman Filter. [PDF]

PLoS One
Lin H, Chen X, Zhang L, Bao Z, Tang S.
europepmc   +1 more source