
Why Deep Networks and Brains Learn Similar Features with Sophia Sanborn - #644
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Optimizing CNNs: Reducing Data Augmentation through Network Structure
This chapter delves into the role of group structures in convolutional neural networks and their potential to minimize reliance on traditional data augmentation. The discussion highlights the balance between network complexity and training efficiency, focusing on how incorporating transformations directly within the network can streamline the training process.
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