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Photography

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Understanding the Impact of Aging on Attractiveness Using a Machine Learning Model of Facial Age Progression.

Facial plastic surgery & aesthetic medicine
Advances in machine learning age progression technology offer the unique opportunity to better understand the public's perception on the aging face. To compare how observers perceive attractiveness and traditional gender traits in faces created wit...

Deep Learning-based Prediction of Axial Length Using Ultra-widefield Fundus Photography.

Korean journal of ophthalmology : KJO
PURPOSE: To develop a deep learning model that can predict the axial lengths of eyes using ultra-widefield (UWF) fundus photography.

Using deep learning to detect diabetic retinopathy on handheld non-mydriatic retinal images acquired by field workers in community settings.

Scientific reports
Diabetic retinopathy (DR) at risk of vision loss (referable DR) needs to be identified by retinal screening and referred to an ophthalmologist. Existing automated algorithms have mostly been developed from images acquired with high cost mydriatic ret...

Combining convolutional neural networks and self-attention for fundus diseases identification.

Scientific reports
Early detection of lesions is of great significance for treating fundus diseases. Fundus photography is an effective and convenient screening technique by which common fundus diseases can be detected. In this study, we use color fundus images to dist...

Monitoring and Identification of Road Construction Safety Factors via UAV.

Sensors (Basel, Switzerland)
The safety of road construction is one of the most important concerns of construction managers for the following reasons: long-span construction operation, no fixed monitoring cameras, and huge impacts on existing traffic, while the managers still re...

A multi-feature deep learning system to enhance glaucoma severity diagnosis with high accuracy and fast speed.

Journal of biomedical informatics
Glaucoma is the leading cause of irreversible blindness, and the early detection and timely treatment are essential for glaucoma management. However, due to the interindividual variability in the characteristics of glaucoma onset, a single feature is...

We got nuts! use deep neural networks to classify images of common edible nuts.

Nutrition and health
BACKGROUND: Nuts are nutrient-dense foods that contribute to healthier eating. Food image datasets enable artificial intelligence (AI) powered diet-tracking apps to help people monitor daily eating patterns.

A deep learning model established for evaluating lid margin signs with colour anterior segment photography.

Eye (London, England)
OBJECTIVES: To evaluate the feasibility of applying a deep learning model to identify lid margin signs from colour anterior segment photography.

A Deep Learning Framework for Earlier Prediction of Diabetic Retinopathy from Fundus Photographs.

BioMed research international
Diabetic patients can also be identified immediately utilizing retinopathy photos, but it is a challenging task. The blood veins visible in fundus photographs are used in several disease diagnosis approaches. We sought to replicate the findings publi...

Research on Multicamera Photography Image Art in BERT Motion Based on Deep Learning Mode.

Computational intelligence and neuroscience
In order to improve the artistic expression effect of photographic images, this article combines the deep learning model to conduct multicamera photographic image art research in BERT motion. Moreover, this article analyzes the external parameter err...