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In this paper, we present a deep learning network to improve the model interpretability, which consists three main modules: deep feature extraction, visual ...
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Abstract—Cataract is a chronic eye disease that causes ir- reversible vision loss. Automatic cataract detection can help people prevent visual impairment ...
A deep learning network to improve the model interpretability, which consists three main modules: deep feature extraction, visual saliency module and ...
In this paper, we present a deep learning network to improve the model interpretability, which consists three main modules: deep feature extraction, visual ...
Duration: 15:37
Posted: Oct 8, 2021
Posted: Oct 8, 2021
Jan 29, 2019 · Cataract is defined as a lenticular opacity presenting usually with poor visual acuity. It is considered the most common cause of blindness.
A multi-level attention network is proposed for cataract classification task. •. Global-level subnet aims to learn global structure features.
It is demonstrated in this paper that the DCNN classifier outperforms state-of-the-art in the performance, and has the potential to be applied to other eye ...
We develop an algorithm and platform to automatically diagnose and grade cataract based on fundus images of patients. This method can help government assisting ...
This survey provides a comprehensive survey of recent advances in machine learning techniques for cataract classification/grading based on ophthalmic images. We ...