Thermal face recognition under different conditions.

Background: A thermal face recognition under different conditions is proposed in this article. The novelty of the proposed method is applying temperature information in the recognition of thermal face. The physiological information is obtained from the face using a thermal camera, and a machine learning classifier is utilized for thermal face recognition.

Transforming Retinal Photographs to Entropy Images in Deep Learning to Improve Automated Detection for Diabetic Retinopathy.

Entropy images, representing the complexity of original fundus photographs, may strengthen the contrast between diabetic retinopathy (DR) lesions and unaffected areas. The aim of this study is to compare the detection performance for severe DR between original fundus photographs and entropy images by deep learning. A sample of 21,123 interpretable fundus photographs obtained from a publicly available data set was expanded to 33,000 images by rotating and flipping.