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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Proceedings ArticleDOI
Active Path Clearing Navigation through Environment Reconfiguration in Presence of Movable Obstacles
TL;DR: A novel path clearing algorithm capable of dealing with ordered manipulations of multiple movable obstacles to provide locally optimal navigation solution is developed.
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Data augmentation and feature selection for automatic model recommendation in computational physics
TL;DR: Two algorithms are introduced, one for dimensionality reduction via feature selection, and one for data augmentation, which enable reaching an accuracy of 90% on the classification problem for nonlinear structural mechanics.
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Visual content representation and retrieval for Cognitive Cyber Physical Systems
TL;DR: A multi-domain knowledge structure based on experience is presented, which can be used as a comprehensive embedded knowledge representation for C-CPS, addressing the representation of visual content issue and facilitating its reuse.
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Precision Chemical Weed Management Strategies: A Review and a Design of a New CNN-Based Modular Spot Sprayer
TL;DR: In this paper , the authors present a survey of different commercial technologies and prototypes for precision patch spraying and spot spraying and compare their performance with those of the same authors in their own work.
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Efficient ensemble for image-based identification of Pneumonia utilizing deep CNN and SGD with warm restarts
TL;DR: In this article , an ensemble method based on stochastic gradient descent with warm restarts (SGDRE) was proposed to address the issues of generalization, dataset size and time complexity.
References
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Deep Residual Learning for Image Recognition
TL;DR: In this article, the authors proposed a residual learning framework to ease the training of networks that are substantially deeper than those used previously, which won the 1st place on the ILSVRC 2015 classification task.
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Adam: A Method for Stochastic Optimization
Diederik P. Kingma,Jimmy Ba +1 more
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Proceedings Article
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan,Andrew Zisserman +1 more
TL;DR: In this paper, the authors investigated the effect of the convolutional network depth on its accuracy in the large-scale image recognition setting and showed that a significant improvement on the prior-art configurations can be achieved by pushing the depth to 16-19 layers.
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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.