Adult content classification through deep convolution neural network
| Autor: | Septian Cahyadi, Febri Damatraseta, Adi Nurhadiyatna, Yan Rianto |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Artificial neural network
business.industry Computer science Domain Name System Feature extraction ComputingMilieux_PERSONALCOMPUTING Process (computing) 020207 software engineering 02 engineering and technology Machine learning computer.software_genre Convolutional neural network Personal computer 0202 electrical engineering electronic engineering information engineering Leverage (statistics) 020201 artificial intelligence & image processing Artificial intelligence business Autonomous system (mathematics) computer |
| Zdroj: | 2017 International Conference on Computer, Control, Informatics and its Applications (IC3INA). |
| DOI: | 10.1109/ic3ina.2017.8251749 |
| Popis: | Adult content filtering is one of the main challenge in Indonesia to prevent children from accessing the adult content. Conventional web blocking and filtering through domain name server filtering is not enough to prevent the adult content distribution. Mobile phones, tablet, and personal computer can distribute the adult content through the offline way. In this case, a more sophisticated and autonomous system is needed that can detect the adult content automatically. To leverage this problem, a deep neural network is used to build a model that is able to detect adult content automatically. In this experiments, our model is able to detect adult content with an accuracy of 75, 08% and 69, 02% during the validation and testing process, respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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