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迈向:人工智能赋能的人工视觉治疗无法治愈的失明。

Towards a: AI-powered artificial vision for the treatment of incurable blindness.

机构信息

Department of Computer Science,University of California,Santa Barbara, CA, United States of America.

Department of Psychological & Brain Sciences, University of California, Santa Barbara, CA, United States of America.

出版信息

J Neural Eng. 2022 Dec 7;19(6). doi: 10.1088/1741-2552/aca69d.

Abstract

How can we return a functional form of sight to people who are living with incurable blindness? Despite recent advances in the development of visual neuroprostheses, the quality of current prosthetic vision is still rudimentary and does not differ much across different device technologies.Rather than aiming to represent the visual scene as naturally as possible, acould provide visual augmentations through the means of artificial intelligence-based scene understanding, tailored to specific real-world tasks that are known to affect the quality of life of people who are blind, such as face recognition, outdoor navigation, and self-care.Complementary to existing research aiming to restore natural vision, we propose a patient-centered approach to incorporate deep learning-based visual augmentations into the next generation of devices.The ability of a visual prosthesis to support everyday tasks might make the difference between abandoned technology and a widely adopted next-generation neuroprosthetic device.

摘要

我们如何能为那些患有不治之盲的人恢复正常的视力呢?尽管在视觉神经假体的发展方面最近取得了进展,但目前的假体视力质量仍然很基础,不同的设备技术之间并没有太大的区别。我们的目标不是尽可能自然地呈现视觉场景,而是可以通过基于人工智能的场景理解来提供视觉增强,针对已知会影响盲人生活质量的特定现实世界任务,例如人脸识别、户外导航和自我护理。与旨在恢复自然视力的现有研究相辅相成,我们提出了一种以患者为中心的方法,将基于深度学习的视觉增强纳入下一代设备中。视觉假体支持日常任务的能力可能会使这项技术从被抛弃变为被广泛采用的下一代神经假体设备。

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