圖像識別3-VGGNet-very deep convolutional Network for large-scale image recognition
文章重點： 1.使用更小的3*3的卷積核與更深的網絡（16-19層）獲得了比ZFNet和AlexNet更好的效果，並且作者測試了不同的數據集證明了該網絡具有很好的泛化性，在其他的測試集上也表現出了很好的性能。 2.作者對比了5種深度的卷積網絡證明深度越深，在訓練數據越大的情況下效果越好。 3.使用了多尺度縮放數據增強技術，證明效果比單尺度數據增強效果提高接近%1. 4.網絡的配置：在訓練階段，卷積
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- 6. VGG——Very deep convolutional networks for large-scale image recognition
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相關文章
- 1. VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 2. Very Deep Convolutional Networks for Large-Scale Image Recognition
- 3. VGG: VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 4. Very Deep Convolutional NetWorks for Large-Scale Image Recognition
- 5. VGGNet：Very Deep Convolutional Networks for Large-Scale Image Recognition
- 6. VGG——Very deep convolutional networks for large-scale image recognition
- 7. VGG--VERY DEEP CONVOLUTIONAL NETWORKS FOR LARGE-SCALE IMAGE RECOGNITION
- 8. VGG——Very Deep Convolution Network for Large-Scale Image Recognition
- 9. 總結Deep Convolutional Neural Network for Image Deconvolution
- 10. ResNet--Deep Residual Learning for Image Recognition