Instagram Hashtag Prediction Using Deep Neural Networks

被引：1

作者：

Beketova, Anna ^{[1
]}

Makarov, Ilya ^{[1
,2
]}

机构：

[1] HSE Univ, Moscow, Russia

[2] Artificial Intelligence Res Inst, Moscow, Russia

来源：

ADVANCES IN COMPUTATIONAL INTELLIGENCE (IWANN 2021), PT II | 2021年 / 12862卷

关键词：

Deep learning; Multi-label image classification; Knowledge distillation; Multimedia;

D O I：

10.1007/978-3-030-85099-9_3

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Instagram is one of the most popular photos sharing services. For more convenient content search people use hashtags (#nature, #love, etc.) in posts with photos. The author's aim is to make hashtag prediction possible and convenient for users. The paper provides a reader with a detailed theoretical overview of Multi-Label Image Classification, Knowledge Distillation, and an overview of ResNet architecture. Next, the author proposes improvements on ResNet architecture allowing the model to boost quality and converge faster. Finally, the model type Self-Improving-Modified-Resnet (SIMR) is presented. Their main feature is the additional bottleneck block used as the tool incorporating benefits from a combination of self-training and knowledge distillation.

引用

页码：28 / 42

页数：15

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