Small Object Detection for Indoor Assistance to the Blind using YOLO NAS Small and Super Gradients

Fuente: arXiv
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Main Authors: BN, Rashmi, Guru, R., A, Anusuya M
Format: Preprint
Published: 2024
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author BN, Rashmi
Guru, R.
A, Anusuya M
author_facet BN, Rashmi
Guru, R.
A, Anusuya M
contents Advancements in object detection algorithms have opened new avenues for assistive technologies that cater to the needs of visually impaired individuals. This paper presents a novel approach for indoor assistance to the blind by addressing the challenge of small object detection. We propose a technique YOLO NAS Small architecture, a lightweight and efficient object detection model, optimized using the Super Gradients training framework. This combination enables real-time detection of small objects crucial for assisting the blind in navigating indoor environments, such as furniture, appliances, and household items. Proposed method emphasizes low latency and high accuracy, enabling timely and informative voice-based guidance to enhance the user's spatial awareness and interaction with their surroundings. The paper details the implementation, experimental results, and discusses the system's effectiveness in providing a practical solution for indoor assistance to the visually impaired.
format Preprint
id arxiv_https___arxiv_org_abs_2409_07469
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Small Object Detection for Indoor Assistance to the Blind using YOLO NAS Small and Super Gradients
BN, Rashmi
Guru, R.
A, Anusuya M
Computer Vision and Pattern Recognition
Artificial Intelligence
Advancements in object detection algorithms have opened new avenues for assistive technologies that cater to the needs of visually impaired individuals. This paper presents a novel approach for indoor assistance to the blind by addressing the challenge of small object detection. We propose a technique YOLO NAS Small architecture, a lightweight and efficient object detection model, optimized using the Super Gradients training framework. This combination enables real-time detection of small objects crucial for assisting the blind in navigating indoor environments, such as furniture, appliances, and household items. Proposed method emphasizes low latency and high accuracy, enabling timely and informative voice-based guidance to enhance the user's spatial awareness and interaction with their surroundings. The paper details the implementation, experimental results, and discusses the system's effectiveness in providing a practical solution for indoor assistance to the visually impaired.
title Small Object Detection for Indoor Assistance to the Blind using YOLO NAS Small and Super Gradients
topic Computer Vision and Pattern Recognition
Artificial Intelligence
url https://arxiv.org/abs/2409.07469