<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">PBES</journal-id><journal-title-group><journal-title>Proceedings of Business and Economic Studies</journal-title></journal-title-group><issn>2209-2641</issn><eissn>2209-265X</eissn><publisher><publisher-name>Bio-Byword Scientific Publishing Pty. Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.26689/pbes.v4i3.2203</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>A Study on Intelligent Guide Stick Using YOLOv3 Algorithm – Improving Spatial Awareness with Self-made Data Set</title><url>https://artdesignp.com/journal/PBES/4/3/10.26689/pbes.v4i3.2203</url><author>YanStone-</author><pub-date pub-type="publication-year"><year>2021</year></pub-date><volume>4</volume><issue>3</issue><history><date date-type="pub"><published-time>2021-06-18</published-time></date></history><abstract>The increasing negligence of “blind lanes” on streets in metropolises such as Shanghai is an inconvenience to the blind population, therefore, alternatives should be explored. When walking on these lanes, there should not be any obstacles for the users, yet bikes can be seen parked there in addition to littered objects. This makes it potentially more dangerous to walk on them in comparison to walking on non-tactile paved lanes. An alternative to these lanes has been discovered which is a camera that is attached to a blind staff. This camera provides auditory feedbacks in regard to the user’s surroundings. Using YOLOv3 (You Only Look Once, Version 3), the software is trained using 140 images to identify three different classes which are blind lanes, waist-high obstacles, and dog feces, as well as the right direction of these objects. If the camera captures any of these three categories, it will provide and voice feedback, hence, warning the user. With this system, the blind can essentially have functional vision that would better guarantee their safety when walking on streets.</abstract><keywords/></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>2018. China country report to world blind union Asia Pacific, general assembly, Ulaanbaatar, Mongolia. World Blind Union Asia Pacific. From: https://wbuap.org/archives/1416</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B2" content-type="article"><label>2</label><element-citation publication-type="journal"><p>Brownlee J, 2019, A gentle introduction to object recognition with deep learning. Machine Learning Mastery. From: https://machinelearningmastery.com/object-recognition-with-deep-learning/</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B3" content-type="article"><label>3</label><element-citation publication-type="journal"><p>Rezatofighi H, et al., 2019, Generalized intersection over union: a metric and a loss for bounding box regression. Computer Vision Foundation. From: https://openaccess.thecvf.com/content_CVPR_2019/papers/Rezatofighi_Generalized_Intersection_Over_Union_A_Metric_and_a_Loss_for_CVPR_2019_paper.pdf</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B4" content-type="article"><label>4</label><element-citation publication-type="journal"><p>Redmon J, Farhadi A, 2020, YOLOv3: an incremental improvement. University of Washington. From: https://pjreddie.com/media/files/papers/YOLOv3.pdf</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B5" content-type="article"><label>5</label><element-citation publication-type="journal"><p>Skalski P, 2019, Gentle dive into math behind convolutional neural networks. Towards Data Science. From: https://towardsdatascience.com/gentle-dive-into-math-behind-convolutional-neural-networks-79a07dd44cf9</p><pub-id pub-id-type="doi"/></element-citation></ref><ref id="B6" content-type="article"><label>6</label><element-citation publication-type="journal"><p>Zhang Y, et al., 2015, Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction. Computer Vision Foundation. From: https://openaccess.thecvf.com/content_cvpr_2015/papers/Zhang_Improving_Object_Detection_2015_CVPR_paper.pdf</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
