کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6957982 1451923 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A Deep Residual convolutional neural network for facial keypoint detection with missing labels
ترجمه فارسی عنوان
یک شبکه عصبی کانولوشن عمیق باقی مانده برای شناسایی کلیدی چهره با برچسب های گم شده
کلمات کلیدی
یادگیری عمیق، تشخیص کلید کلیدی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
Keypoint detection is critical in image recognitions. Deep learning such as convolutional neural network (CNN) has recently demonstrated its tremendous success in detecting image keypoints over conventional image processing methodologies. The deep learning solutions, however, heavily rely on labeling target images for their reliability and accuracy. Unfortunately, most image datasets do not have all labels marked. To address this problem, this paper presents an effective and novel deep learning solution, Masked Loss Residual Convolutional Neural Network (ML-ResNet), to facial keypoint detection on the datasets that have missing target labels. The core of ML-ResNet is a masked loss objective function that ignores the error in predicting the missing target keypoints in the output layer of a CNN. To compensate for the loss induced by the masked loss objective function that likely results in overfitting, ML-ResNet is designed of a data augmentation strategy to increase the number of training data. The performance of ML-ResNet has been evaluated on the image dataset from Kaggle Facial Keypoints Detection competition, which consists of 7049 training images, but with only 2140 images that have full target keypoints labeled. In the experiments, ML-ResNet is compared to a pioneer literature CNN facial keypoint detection work. The experiment results clearly show that the proposed ML-ResNet is robust and advantageous in training CNNs on datasets with missing target values. ML-ResNet can improve the learning time by 30% during the training and the detection accuracy by eight times in facial keypoint detection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Signal Processing - Volume 144, March 2018, Pages 384-391
نویسندگان
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