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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Journal ArticleDOI
Deep Learning for Generic Object Detection: A Survey
Li Liu,Li Liu,Wanli Ouyang,Xiaogang Wang,Paul Fieguth,Jie Chen,Xinwang Liu,Matti Pietikäinen +7 more
TL;DR: A comprehensive survey of the recent achievements in this field brought about by deep learning techniques, covering many aspects of generic object detection: detection frameworks, object feature representation, object proposal generation, context modeling, training strategies, and evaluation metrics.
Journal ArticleDOI
A survey of the recent architectures of deep convolutional neural networks
TL;DR: Deep Convolutional Neural Networks (CNNs) as mentioned in this paper are a special type of Neural Networks, which has shown exemplary performance on several competitions related to Computer Vision and Image Processing.
Journal ArticleDOI
Applications of machine learning to machine fault diagnosis: A review and roadmap
TL;DR: A review and roadmap to systematically cover the development of IFD following the progress of machine learning theories and offer a future perspective is presented.
Journal ArticleDOI
Review of deep learning: concepts, CNN architectures, challenges, applications, future directions
Laith Alzubaidi,Jinglan Zhang,Amjad J. Humaidi,Ayad Q. Al-Dujaili,Ye Duan,Omran Al-Shamma,José Santamaría,Mohammed A. Fadhel,Muthana Al-Amidie,Laith Farhan +9 more
TL;DR: In this paper, a comprehensive survey of the most important aspects of DL and including those enhancements recently added to the field is provided, and the challenges and suggested solutions to help researchers understand the existing research gaps.
Journal ArticleDOI
Albumentations: fast and flexible image augmentations
Alexander Buslaev,Vladimir Iglovikov,Eugene Khvedchenya,Alex Parinov,Mikhail Druzhinin,Alexandr A. Kalinin +5 more
TL;DR: Albumentations as mentioned in this paper is a fast and flexible open source library for image augmentation with many various image transform operations available that is also an easy-to-use wrapper around other augmentation libraries.
References
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Bilinear CNN Models for Fine-grained Visual Recognition
TL;DR: This paper proposed bilinear models, which consists of two feature extractors whose outputs are multiplied using outer product at each location of the image and pooled to obtain an image descriptor, which can model local pairwise feature interactions in a translationally invariant manner.
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