| ITI əməkdaşlarının elmi işləri - məqalə |
| Biblioqrafik təsvir | |
| Alguliyev , R.M. Image-based malicious Internet content filtering method for child protection / R.M. Alguliyev , F.D. Abdullayeva , S.S. Ojagverdiyeva // Journal of Information Security and Applications . - 2022. - N: 65.- P. 1-10. | |
| Annotasiya | |
| Children and teenagers are among Internet users and they encounter harmful data in the global network. Young users often become the potential victims of pornographic images. Avoiding pornographic images harmful to the child audience is an important research task in the field of detection, computer vision and multimedia. Malicious content can be prevented using various methods. Current paper presents a ChildNet model that filters harmful image content. The pixels of the digital images are used as a data source for recognition of nudity in the images. For each class, a multi-layer deep neural network architecture with five convolution blocks is developed to study the color patterns of undesirable image pixels. The developed neural network consists of 21 layers; the size of the filters is specified as (3 × 3). The filter’s size is reduced to increase the accuracy of pixel recognition. The efficiency of the proposed method is tested on real datasets for evaluation purposes and the superior results are obtained from the proposed method in comparison with classical CNN. | |
| Elektron variant | |
| Elektron variant |
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