Going deeper with convolutions
@article{Szegedy2015GoingDW, title={Going deeper with convolutions}, author={Christian Szegedy and W. Liu and Y. Jia and Pierre Sermanet and Scott E. Reed and Dragomir Anguelov and D. Erhan and V. Vanhoucke and Andrew Rabinovich}, journal={2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, year={2015}, pages={1-9} }
We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Scale Visual Recognition Challenge 2014 (ILSVRC14). The main hallmark of this architecture is the improved utilization of the computing resources inside the network. By a carefully crafted design, we increased the depth and width of the network while keeping the computational budget constant. To optimize quality, the… Expand
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⛵️ Implementation a variety of popular Image Classification Models using TensorFlow2. [ResNet, GoogLeNet, VGG, Inception-v3, Inception-v4, MobileNet, MobileNet-v2, ShuffleNet, ShuffleNet-v2, etc...]
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References
SHOWING 1-10 OF 278 REFERENCES
Some Improvements on Deep Convolutional Neural Network Based Image Classification
- Computer Science
- ICLR
- 2014
- 290
- PDF
Scalable Object Detection Using Deep Neural Networks
- Computer Science, Mathematics
- 2014 IEEE Conference on Computer Vision and Pattern Recognition
- 2014
- 824
- PDF
DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition
- Computer Science
- ICML
- 2014
- 3,771
- PDF
OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks
- Computer Science
- ICLR
- 2014
- 3,825
- PDF
Multi-scale Orderless Pooling of Deep Convolutional Activation Features
- Computer Science
- ECCV
- 2014
- 899
- PDF
ImageNet classification with deep convolutional neural networks
- Computer Science
- Commun. ACM
- 2012
- 60,762
- PDF