mlsanityData to 14 Oct 2026

AIris: An AI-powered Wearable Assistive Device for the Visually Impaired

arXiv 2405.07606 ↗First posted 13 May 2024cs.HC cs.CVcited by 3

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Abstract (arXiv)

Assistive technologies for the visually impaired have evolved to facilitate interaction with a complex and dynamic world. In this paper, we introduce AIris, an AI-powered wearable device that provides environmental awareness and interaction capabilities to visually impaired users. AIris combines a sophisticated camera mounted on eyewear with a natural language processing interface, enabling users to receive real-time auditory descriptions of their surroundings. We have created a functional prototype system that operates effectively in real-world conditions. AIris demonstrates the ability to accurately identify objects and interpret scenes, providing users with a sense of spatial awareness previously unattainable with traditional assistive devices. The system is designed to be cost-effective and user-friendly, supporting general and specialized tasks: face recognition, scene description, text reading, object recognition, money counting, note-taking, and barcode scanning. AIris marks a transformative step, bringing AI enhancements to assistive technology, enabling rich interactions with a human-like feel.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 6 of its 24 references that are in the map. First posted on arXiv 13 May 2024.

Builds on

6 of 24 references.

References · 6

  1. 2015Deep Residual Learning for Image Recognitioncited by 52,096
  2. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  3. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,475
  4. 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,852
  5. 2017State-of-the-art Speech Recognition With Sequence-to-Sequence Modelscited by 196
  6. 2019Model Asset eXchange: Path to Ubiquitous Deep Learning Deploymentcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.