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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Machine learning and deep learning for clinical data and PET/SPECT imaging in Parkinson's disease: a review
TL;DR: An overview of the application of hand-crafted ML algorithms and DL techniques for PD diagnosis can be found in this paper, where the authors also introduce key concepts for understanding the application and application of ML methods to diagnose PD.
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Prediction of tram track gauge deviation using artificial neural network and support vector regression
TL;DR: In this study, the Melbourne tram network is considered as a case study and two machine learning models including artificial neural network (ANN) and support vector machine (SVM) are applied.
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MRI radiogenomics for intelligent diagnosis of breast tumors and accurate prediction of neoadjuvant chemotherapy responses-a review
TL;DR: In this article , a Generative Adiversarial Networks (GAN) based deep learning strategy is proposed for the classification of tumour types; this has significant potential for providing accurate real-time identification of tumorous regions from MRI scans.
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Image Interpolation Using Multi-Scale Attention-Aware Inception Network
TL;DR: Extensive experimental simulation results obtained from seven image datasets have clearly shown that the proposed MAIN consistently delivers highly accurate interpolated images.
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Recent Techniques and Trends for Retinal Blood Vessel Extraction and Tortuosity Evaluation: A Comprehensive Review
TL;DR: This article presents a comprehensive overview of all segmentation techniques for retinal blood vessel extraction from images taken with a fundus camera in adults and older children or with a RetCam fundu camera in new-borns and younger children over the last 10 years.
References
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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.