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Knowledge Distillation in Image Classification: The Impact of Datasets

https://doi.org/10.3390/computers13080184

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What this work says

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Soft Hybrid Knowledge Distillation against deep neural networks

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Ambiguity-aware robust teacher (ART): Enhanced self-knowledge distillation framework with pruned teacher network

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Dual teachers for self-knowledge distillation

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An Analysis Of Convolutional Neural Networks For Image Classification

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Time Complexity in Deep Learning Models

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Unbiased look at dataset bias

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Deep Residual Learning for Image Recognition

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A Gift from Knowledge Distillation: Fast Optimization, Network Minimization and Transfer Learning

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Data Distillation: Towards Omni-Supervised Learning

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Collaborative Distillation for Ultra-Resolution Universal Style Transfer

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Understanding of a convolutional neural network

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Triplet Distillation For Deep Face Recognition

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The MNIST Database of Handwritten Digit Images for Machine Learning Research [Best of the Web]

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Representation Learning: A Review and New Perspectives

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Deep Convolutional Neural Networks for Image Classification: A Comprehensive Review

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A survey on Image Data Augmentation for Deep Learning

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Improved Knowledge Distillation via Teacher Assistant

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TinyBERT: Distilling BERT for Natural Language Understanding

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Layer-Level Knowledge Distillation for Deep Neural Network Learning

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What Makes a "Good" Data Augmentation in Knowledge Distillation - A Statistical Perspective

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What Knowledge Gets Distilled in Knowledge Distillation?

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Learning Multiple Layers of Features from Tiny Images

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