Results 251 to 260 of about 232,443 (272)

Optimizing Convolutional Neural Networks for Perspiration Rate Sensing in Wearable Devices

Pratyashi Satapathy
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Enhanced deep Convolutional Neural Network for SARS-CoV-2 variants classification. [PDF]

Front Artif Intell
Awe OI, Obura H, Ssemuyiga C, Mudibo E, Mwanga MJ.   +4 more
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Enhancing museum collection images with fuzzy set guided convolutional neural network: A novel approach leveraging fuzzy set theory

Manqi Li, Lili Ren
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Accurate prediction of protein-ATP binding sites based on a protein pretrained large language model and a fractional-order convolutional neural network. [PDF]

Sci Rep
Guo M, Tu Y, Yu J, Wang Y.
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DSSCC net enhanced skin cancer classification using SMOTE Tomek and optimized convolutional neural network. [PDF]

Sci Rep
Javaid MA, Shahzad MS, Shehzad HMF, Razzaq S, Ali S, Shah D, Tahir M.   +6 more
europepmc   +1 more source

From Convolutional Neural Networks to Vision Foundation Models: A Comprehensive Review of Intelligent Evolution in Computer Vision

Xiwei Luo
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Convolutional Neural Networks

2023
Dieses Kapitel führt in Convolutional Neural Networks (CNNs) ein und beschreibt, wie diese im Kontext der Sportanalyse verwendet werden können. Insbesondere eignen sich CNNs für das End-to-End-Lernen auf Bildern oder ähnlich strukturierten Daten. Dabei können CNNs Merkmale von Bildern anhand der Pixelwerte effizient lernen und beispielsweise sehr gute ...
Teik Toe Teoh, Yu Jin Goh
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Convolutional Neural Network

2021
Convolutional neural network (CNN) is a (Agrawal and Roy, IEEE Trans Magn 55:1–7, 2019) class of deep neural network. CNNs are what we call the most representative supervised model in the theory of deep learning is the technique that nowadays (Akinaga and Shima, Proc IEEE 98:2237–2251, 2010) is producing a lot of outstanding results especially in the ...
Y. V. R. Nagapawan, Kolla Bhanu Prakash, G. R. Kanagachidambaresan   +2 more
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Differential convolutional neural network

Neural 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.
Sarıgül M., Ozyildirim B.M., Avci M.
openaire   +3 more sources