Real Time Eye Detector with Cascaded Convolutional Neural Networks
An accurate and efficient eye detector is essential for many computer vision applications. In this paper, we present an efficient method to evaluate the eye location from facial images. First, a group of candidate regions with regional extreme points is quickly proposed; then, a set of convolution n...
Saved in:
| Main Authors: | Bin Li, Hong Fu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
|
| Series: | Applied Computational Intelligence and Soft Computing |
| Online Access: | http://dx.doi.org/10.1155/2018/1439312 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Crack Detection Method of Sleeper Based on Cascade Convolutional Neural Network
by: Liming Li, et al.
Published: (2022-01-01) -
A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection
by: Noppadol Maneerat, et al.
Published: (2025-06-01) -
A Ship Detector Design Based on Deep Convolutional Neural Networks for Satellite Images
by: Ferhat Ucar, et al.
Published: (2020-02-01) -
Real-Time Road Crack Mapping Using an Optimized Convolutional Neural Network
by: M-Mahdi Naddaf-Sh, et al.
Published: (2019-01-01) -
CacPred: a cascaded convolutional neural network for TF-DNA binding prediction
by: Shuangquan Zhang, et al.
Published: (2025-03-01)