We extend earlier work on detecting pornographic images. Our focus is on the classification stage and we give new results for a variety of classical and modern classifiers. We find the artificial neural network offers a statistically significant improvement. In all cases the error rate is too high unless deployed sensitively so we show how such a system may be built into a commercial environment.
|Name||Lecture Notes in Computer Science|
|Publisher||Springer Berlin / Heidelberg|
|Conference||International Conference on Image and Video Retrieval|
|Period||18/07/02 → 19/07/02|