تقرير
Coloring Deep CNN Layers with Activation Hue Loss
العنوان: | Coloring Deep CNN Layers with Activation Hue Loss |
---|---|
المؤلفون: | Bouchard, Louis-François, Lazreg, Mohsen Ben, Toews, Matthew |
سنة النشر: | 2023 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
الوصف: | This paper proposes a novel hue-like angular parameter to model the structure of deep convolutional neural network (CNN) activation space, referred to as the {\em activation hue}, for the purpose of regularizing models for more effective learning. The activation hue generalizes the notion of color hue angle in standard 3-channel RGB intensity space to $N$-channel activation space. A series of observations based on nearest neighbor indexing of activation vectors with pre-trained networks indicate that class-informative activations are concentrated about an angle $\theta$ in both the $(x,y)$ image plane and in multi-channel activation space. A regularization term in the form of hue-like angular $\theta$ labels is proposed to complement standard one-hot loss. Training from scratch using combined one-hot + activation hue loss improves classification performance modestly for a wide variety of classification tasks, including ImageNet. |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2310.03911 |
رقم الأكسشن: | edsarx.2310.03911 |
قاعدة البيانات: | arXiv |
كن أول من يترك تعليقا!