Assistive Technology for Visually Impaired using Tensor Flow Object Detection in Raspberry Pi and Coral USB Accelerator

Amit Ghosh, Shamsul Arefeen Al Mahmud, Thajid Ibna Rouf Uday, Dewan Md. Farid

Tutkimustuotos: Artikkeli kirjassa/konferenssijulkaisussaConference article in proceedingsScientificvertaisarvioitu

7 Sitaatiot (Scopus)
291 Lataukset (Pure)

Abstrakti

Assistive Technology (AT) becomes an interesting field of research in this present era. According to the World Health Organisation (WHO - https://www.who.int), there are approximately 285 million visually impaired people around the world. To address this issue, many researchers are employing new technologies, e.g. Machine Learning (ML), Computer Vision (CV), Image Processing, etc. This paper aims to develop an assistive technology based on Computer Vision, Machine Learning and Tensor Flow to support visually impaired people. The proposed system will allow the users to navigate independently using real-time object detection and identification. Hardware implementation is done to test the performance of the system, and the performance is tracked using a monitoring server. The system is developed on Raspberry pi 4 and a dedicated server with NVIDIA Titan X graphics where Google coral USB accelerator is used to boost processing power.

AlkuperäiskieliEnglanti
OtsikkoProceedings of the 2020 IEEE Region 10 Symposium, TENSYMP 2020
KustantajaIEEE
Sivut186-189
Sivumäärä4
ISBN (elektroninen)9781728173665
DOI - pysyväislinkit
TilaJulkaistu - 5 kesäk. 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIEEE Region 10 Symposium - Virtual, Dhaka, Bangladesh
Kesto: 5 kesäk. 20207 kesäk. 2020

Conference

ConferenceIEEE Region 10 Symposium
LyhennettäTENSYMP
Maa/AlueBangladesh
KaupunkiDhaka
Ajanjakso05/06/202007/06/2020

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