ImageNet classification with deep convolutional neural networks
@article{Krizhevsky2012ImageNetCW, title={ImageNet classification with deep convolutional neural networks}, author={A. Krizhevsky and Ilya Sutskever and Geoffrey E. Hinton}, journal={Communications of the ACM}, year={2012}, volume={60}, pages={84 - 90} }
We trained a large, deep convolutional neural network to classify the 1.2 million high-resolution images in the ImageNet LSVRC-2010 contest into the 1000 different classes. [...] Key Method The neural network, which has 60 million parameters and 650,000 neurons, consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.Expand
Supplemental Content
Presentation Slides
ImageNet classification with deep convolutional neural networks
Figures and Topics from this paper
61,085 Citations
Convolutional networks with cross-layer neurons for image recognition
- Computer Science
- Inf. Sci.
- 2018
- 20
Understanding of a convolutional neural network
- Computer Science
- 2017 International Conference on Engineering and Technology (ICET)
- 2017
- 234
Image Classification Based on the Boost Convolutional Neural Network
- Computer Science
- IEEE Access
- 2018
- 39
An Efficient Deep Convolutional Neural Network for Visual Image Classification
- Computer Science
- AMLTA
- 2019
- 11
Tree-CNN: A Deep Convolutional Neural Network for Lifelong Learning
- Computer Science, Engineering
- ArXiv
- 2018
- 22
- PDF
Learning Filter Basis for Convolutional Neural Network Compression
- Computer Science
- 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
- 2019
- 18
- PDF
References
ImageNet: A large-scale hierarchical image database
- Computer Science
- CVPR
- 2009
- 16,231
- Highly Influential
- PDF