Abstract:
Freckles is a facial feature of human, it has many significant applications in many video surveillance area. This paper proposes to use deep learning method to perform fr...Show MoreMetadata
Abstract:
Freckles is a facial feature of human, it has many significant applications in many video surveillance area. This paper proposes to use deep learning method to perform freckles detection and recognition in face images. To be more specific, a freckle recognition model is proposed in this paper based on convolution neural network. Experimental results are presented to show that the proposed approach is able to achieve 98% accuracy freckle recognition rate.
Published in: 2017 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS)
Date of Conference: 06-09 November 2017
Date Added to IEEE Xplore: 22 January 2018
ISBN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Convolutional Neural Network ,
- Face Recognition ,
- Freckles ,
- Deep Learning ,
- Facial Features ,
- Face Images ,
- Recognition Rate ,
- Learning Rate ,
- Positive Samples ,
- Convolutional Layers ,
- Computer Vision ,
- Negative Samples ,
- Learning Curve ,
- Image Size ,
- Data Preparation ,
- Pooling Layer ,
- Part Of The Image ,
- Local Image ,
- Input Size ,
- Human Faces ,
- AlexNet ,
- Face Area
- Author Keywords
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Convolutional Neural Network ,
- Face Recognition ,
- Freckles ,
- Deep Learning ,
- Facial Features ,
- Face Images ,
- Recognition Rate ,
- Learning Rate ,
- Positive Samples ,
- Convolutional Layers ,
- Computer Vision ,
- Negative Samples ,
- Learning Curve ,
- Image Size ,
- Data Preparation ,
- Pooling Layer ,
- Part Of The Image ,
- Local Image ,
- Input Size ,
- Human Faces ,
- AlexNet ,
- Face Area
- Author Keywords
