Forecasting and analyzing influenza activity in Hebei Province, China, using a CNN-LSTM hybrid model
BMC Public HealthBackground 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 +10 more
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Sensing Mechanism of Cognitive Radio Interference Reduction using Convolution Neural Network (CNN) Based Internet of Things (IOT) [PDF]
The persistent failure in communication network failure were anchored by Received signal to noise ratio, Interference to noise ratio, Interference to signal ratio, Receiver noise figure, and Quantized effect bits that could not attain their ...
Nnadi, P. U +2 more
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Convolution neural network based text image classifications
, 2017 Convolution neural network(CNN) is a sensor with multiple layers, which is designed for identifying 2-dimensional images, with parallel processing ability, self-learning ability and good fault tolerance.
Zhou, Xiang
core
Design Of Neural Network Circuit Inside High Speed Camera Using Analog CMOS 0.35 ¼m Technology [PDF]
, 2009 Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of applications involving industrial as well as consumer appliances. This is particularly the case when low power consumption, small size and/or very high speed
Mukhlis, Yulisdin
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Large receptive field convolutional neural network for image super-resolution
, 2017 This paper presents a new approach to Single Image Super Resolution (SISR), based upon Convolutional Neural Network (CNN). Although the SISR is ill-posed which can be seen as finding a non-linear mapping from a low to high dimensional space.
Wang Q(王强) +3 more
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Lightweight monocular depth estimation using a fusion-improved transformer
Scientific ReportsThe 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 +5 more
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Food Image Recognition by Using Convolutional Neural Networks (CNNs)
CoRR, 2016 Food image recognition is one of the promising applications of visual object recognition in computer vision. In this study, a small-scale dataset consisting of 5822 images of ten categories and a five-layer CNN was constructed to recognize these images.
openaire +2 more sources
CNN-LSTM network feature extraction process.
To accurately locate faulty components in analog circuits, an analog circuit fault diagnosis method based on Tunable Q-factor Wavelet Transform(TQWT) and Convolutional Neural Network (CNN) is proposed in this paper. Firstly, the Grey Wolf algorithm (GWO)
Xuye Zhuang (17935681) +4 more
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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 +3 more
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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 +4 more
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