Recent advances in convolutional neural networks
Jiuxiang Gu,Zhenhua Wang,Jason Kuen,Lianyang Ma,Amir Shahroudy,Bing Shuai,Ting Liu,Xingxing Wang,Gang Wang,Jianfei Cai,Tsuhan Chen +10 more
TLDR
A broad survey of the recent advances in convolutional neural networks can be found in this article, where the authors discuss the improvements of CNN on different aspects, namely, layer design, activation function, loss function, regularization, optimization and fast computation.About:
This article is published in Pattern Recognition.The article was published on 2018-05-01 and is currently open access. It has received 3125 citations till now. The article focuses on the topics: Deep learning & Convolutional neural network.read more
Citations
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The Tabu_Genetic Algorithm: A Novel Method for Hyper-Parameter Optimization of Learning Algorithms
TL;DR: The presented method provides a new solution for solving the hyper-parameters optimization problem of complex machine learning models, which will provide machine learning algorithms with better performance when solving practical problems.
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Modified Gaussian convolutional deep belief network and infrared thermal imaging for intelligent fault diagnosis of rotor-bearing system under time-varying speeds:
TL;DR: A modified Gaussian convolutional deep belief network driven by infrared thermal imaging is proposed to automatically diagnose different faults of rotor-bearing system under time-varying speeds and outperforms the other methods.
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Automatic detection of woody vegetation in repeat landscape photographs using a convolutional neural network
Ulrike Bayr,Oskar Puschmann +1 more
TL;DR: This paper demonstrates the application of a convolutional neural network for the automatic detection and classification of woody regrowth vegetation in repeat landscape photographs and tests if the classification results based on the automatic approach can be used for quantifying changes in woody vegetation cover between image pairs.
Journal ArticleDOI
Intelligent layout design of curvilinearly stiffened panels via deep learning-based method
TL;DR: Numerical examples demonstrate that the proposed intelligent optimization framework significantly improves the optimization efficiency compared to traditional models, and indicates the extraordinary promise of deep learning-based methods in the field of engineering optimization.
Journal ArticleDOI
Social media sentiment analysis through parallel dilated convolutional neural network for smart city applications
TL;DR: This paper proposes a domain-specific distributed word representation (DS-DWR) with a considerably small corpus size induced from textual resources in social media, and considers parallel dilated convolution, which reduces dimension and incorporates an extension in the size of receptive fields without the loss of local information.
References
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Very Deep Convolutional Networks for Large-Scale Image Recognition
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Gradient-based learning applied to document recognition
Yann LeCun,Léon Bottou,Léon Bottou,Yoshua Bengio,Yoshua Bengio,Yoshua Bengio,Patrick Haffner +6 more
TL;DR: In this article, a graph transformer network (GTN) is proposed for handwritten character recognition, which can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters.