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Article . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
ZENODO
Article . 2024
License: CC BY
Data sources: Datacite
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Object Detection and Recognition Using TensorFlow for Blind People

Authors: Darshan A., Mirapure; Dipam, Pakhamode; Prof. Rina, Shirpurkar;

Object Detection and Recognition Using TensorFlow for Blind People

Abstract

Computer Vision impairment or blindness is one such top ten disabilities in humans, and unfortunately, India has the world’s largest visually impaired population. For this we are creating a framework to guide the visually impaired on object detecting and recognition, so that they can navigate without others support, and be safe within their surroundings. In this system the captured image is taken and sent it as input using camera. SSD Architecture is used here for the detection of objects based on deep neural networks to make precise detection. This input will be given to the software and it will be processed under the COCO datasets which are predefined in the Tensor flow library used as training dataset for the system in general this data set consist of features for nighty percent of real world data objects and distance is calculated by depth estimation and also by using voice assistance packages the software will produce the output in the way of Audio. The System is implemented completely using Python Programming Language since python consist of many inbuilt packages and libraries which will make the complication of writing code more number of lines into simple any less number of lines.

Country
Indonesia
Related Organizations
Keywords

000, QA75 Electronic computers. Computer science, 004

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green