Results 11 to 20 of about 250,191 (314)

Artificial Intelligence Image Recognition Method Based on Convolutional Neural Network Algorithm

open access: yesIEEE Access, 2020
As an algorithm with excellent performance, convolutional neural network has been widely used in the field of image processing and achieved good results by relying on its own local receptive fields, weight sharing, pooling, and sparse connections.
Youhui Tian
doaj   +3 more sources

A noise robust convolutional neural network for image classification

open access: yesResults in Engineering, 2021
Convolutional Neural Networks (CNNs) are extensively used for image classification. Noisy images reduce the classification performance of convolutional neural networks and increase the training time of the networks.
Mohammad Momeny   +4 more
doaj   +3 more sources

Differential convolutional neural network [PDF]

open access: yesNeural Networks, 2019
Convolutional neural networks with strong representation ability of deep structures have ever increasing popularity in many research areas. The main difference of Convolutional Neural Networks with respect to existing similar artificial neural networks is the inclusion of the convolutional part.
Mehmet Sarigul   +2 more
openaire   +4 more sources

Contextual Convolutional Neural Networks [PDF]

open access: yes2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021
We propose contextual convolution (CoConv) for visual recognition. CoConv is a direct replacement of the standard convolution, which is the core component of convolutional neural networks. CoConv is implicitly equipped with the capability of incorporating contextual information while maintaining a similar number of parameters and computational cost ...
Ionut Cosmin Duta   +2 more
openaire   +2 more sources

Convolution-Bidirectional Temporal Convolutional Network for Protein Secondary Structure Prediction

open access: yesIEEE Access, 2022
As a basic feature extraction method, convolutional neural networks have some information loss problems when dealing with sequence problems, and a temporal convolutional network can compensate for this problem.
Yunqing Zhang, Yuming Ma, Yihui Liu
doaj   +1 more source

Augmented Reality based 3D Human Hands Tracking from Monocular True Images Using Convolutional Neural Network [PDF]

open access: yes, 2023
Precise modeling of hand tracking from monocular moving camera calibration parameters using semantic cues is an active area of research concern for the researchers due to lack of accuracy and computational overheads.
Saif, A F M Saifuddin   +1 more
core   +1 more source

Improved Convolutional Neural Image Recognition Algorithm based on LeNet-5

open access: yesJournal of Computer Networks and Communications, 2022
Convolutional neural network (CNN) is a very important method in deep learning, which solves many complex pattern recognition problems. Fruitful results have been achieved in image recognition, speech recognition, and natural language processing ...
Lijie Zhou, Weihai Yu
doaj   +1 more source

Texture synthesis of ecological plant protection image based on convolution neural network

open access: yesFrontiers in Plant Science, 2022
Texture synthesis technology is an important realistic rendering technology. Texture synthesis technology also has a good application prospect in image rendering and other fields. Convolutional neural network is a very popular technology in recent years.
Libing Hu, Fei Zhou, Xianjun Fu
doaj   +1 more source

DISTRIBUTED CONVOLUTIONAL NEURAL NETWORK MODEL ON RESOURCE-CONSTRAINED CLUSTER [PDF]

open access: yesНаучно-технический вестник информационных технологий, механики и оптики, 2020
Subject of Research. The paper presents the distributed deep learning particularly convolutional neural network problem for resource-constrained devices.
Rezeda R. Khaydarova   +3 more
doaj   +1 more source

Pansharpening by Convolutional Neural Networks [PDF]

open access: yesRemote Sensing, 2016
A new pansharpening method is proposed, based on convolutional neural networks. We adapt a simple and effective three-layer architecture recently proposed for super-resolution to the pansharpening problem. Moreover, to improve performance without increasing complexity, we augment the input by including several maps of nonlinear radiometric indices ...
MASI, GIUSEPPE   +3 more
openaire   +4 more sources

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