Automated Data Digitization System for Vehicle Registration Certificates Using Google Cloud Vision API

Thammarak, Karanrat; Sirisathitkul, Yaowarat; Kongkla, Prateep; Intakosum, Sarun

doi:10.28991/cej-2022-08-07-09

Cited by 12 publications

(8 citation statements)

References 33 publications

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“…A pre-study was conducted to test and thematically examine the survey design's suitability, and validity; and allow the researchers to enhance its efficiency [86,87]. Then, a pilot test was carried out to develop the measuring equipment [85,88,89].…”

Section: -Research Methodologymentioning

confidence: 99%

Factors Influencing Consumer Acceptance of Mobile Payment during the COVID-19 Pandemic & Usage Continuance Intent: A Quantitative Study

Zaidi,

Ali,

Thanasi-Boçe

2023

Emerg Sci J

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The presence of COVID-19 has transformed the business sector’s paradigm and prompted a speedy consumption of mobile payment software systems of diverse ranges. Corporate sectors and businesses across the globe brought a shift to offer mobile payment methods; consequently, consumers were urged to maximize the use of mobile payment throughout the pandemic. The present research aims to investigate the factors that might influence consumers' intent to accept mobile payments and their relationships during COVID-19. The technology adoption model and the unified theory of acceptance and use of technology were employed in this proposed mobile payment adoption framework. A quantitative research approach was identified as a suitable method for this research. An online survey was administered, and 304 participants responded to the questionnaire. The results of the data analysis revealed statistically significant relationships and a positive impact of the factors perceived performance, social influence, consumers’ satisfaction, and perceived usefulness on consumers’ usage continuation intention. However, the results identified that factors such as transaction risk didn’t affect perceived usefulness, and financial transaction transparency didn’t affect consumers’ usage intention. This study makes a substantial contribution to the consumers’ technology acceptance literature in terms of validating a proposed theoretical framework that highlights the factors that influence consumers’ mobile payment usage intentions. As this study was conducted at a later stage of the COVID-19 pandemic, it adds value to the existing literature by providing insights to business managers on the factors influencing mobile payment usage. Considering the practical perspective, this study offers evidence of the essential elements that mobile payment service designers and marketers should consider. Doi: 10.28991/ESJ-2023-07-05-07 Full Text: PDF

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Section: -Research Methodologymentioning

confidence: 99%

Factors Influencing Consumer Acceptance of Mobile Payment during the COVID-19 Pandemic & Usage Continuance Intent: A Quantitative Study

Zaidi,

Ali,

Thanasi-Boçe

2023

Emerg Sci J

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“…Dalam tahap transformasi tersebut, digitalisasi data fisik seperti gambar, dokumen, dan buku adalah hal yang esensial untuk dilakukan. Dokumen digital dapat digunakan oleh perusahaan untuk menyederhanakan proses dan meningkatkan kualitas layanan dari perusahaan [1]. Pada banyak perusahaan, berbagai proses bisnis membutuhkan kartu identitas sebagai alat verifikasi [2].…”

Section: Latar Belakangunclassified

Analisis Perbandingan Optical Character Recognition Google Vision dengan Microsoft Computer Vision pada Pembacaan KTP-el

Valentino,

Susetyo

2023

jtik

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In this era, the need of digital data is rapidly increasing. Electronic Residental Identity Card or KTP-el is the official identity card for resident of Indonesia. One fast way to extract information on an image is by using OCR/Optical Character Recognition. Competition between Google Vision API and Microsoft Computer Vision in providing OCR service encourage companies to choose the right provider. Method conducted in this research including literature review on both OCR service provider, identification and KTP-el sample image retrieval, data grouping, code implementation and accuracy testing, result analysis and discussion, and conclusion. The result of this research show that Microsoft Computer Vision have better accuracy in reading characters in KTP-el with an accuracy percentage of 0,81% to 15,8% difference to Google Vision. Google Vision has competitive accuracy, but suffers from deficiencies when reading KTP-el with blur and noise.

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“…Previous research by Huu et al [6] and Wu et al [7] have explored the application of YOLOv4 and YOLOv5 object detection algorithms in smart education and complex scene analysis, respectively. Mobile applications designed for visually challenged people enhance their accessibility, object recognition [8,9], social interaction and communication, education and learning, independent living etc. The YOLO (You Only Look Once) object detection algorithm [3,10,11] has evolved, including YOLOv4 [12] and YOLOv5.…”

Section: Com [4])mentioning

confidence: 99%

The Eye: A Light Weight Mobile Application for Visually Challenged People Using Improved YOLOv5l Algorithm

Anbananthen,

Subbiah,

Baskar

et al. 2023

Emerg Sci J

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The eye is an essential sensory organ that allows us to perceive our surroundings at a glance. Losing this sense can result in numerous challenges in daily life. However, society is designed for the majority, which can create even more difficulties for visually impaired individuals. Therefore, empowering them and promoting self-reliance are crucial. To address this need, we propose a new Android application called “The Eye” that utilizes Machine Learning (ML)-based object detection techniques to recognize objects in real-time using a smartphone camera or a camera attached to a stick. The article proposed an improved YOLOv5l algorithm to improve object detection in visual applications. YOLOv5l has a larger model size and captures more complex features and details, leading to enhanced object detection accuracy compared to smaller variants like YOLOv5s and YOLOv5m. The primary enhancement in the improved YOLOv5l algorithm is integrating L1 and L2 regularization techniques. These techniques prevent overfitting and improve generalization by adding a regularization term to the loss function during training. Our approach combines image processing and text-to-speech conversion modules to produce reliable results. The Android text-to-speech module is then used to convert the object recognition results into an audio output. According to the experimental results, the improved YOLOv5l has higher detection accuracy than the original YOLOv5 and can detect small, multiple, and overlapped targets with higher accuracy. This study contributes to the advancement of technology to help visually impaired individuals become more self-sufficient and confident. Doi: 10.28991/ESJ-2023-07-05-011 Full Text: PDF

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Automated Data Digitization System for Vehicle Registration Certificates Using Google Cloud Vision API

Cited by 12 publications

References 33 publications

Factors Influencing Consumer Acceptance of Mobile Payment during the COVID-19 Pandemic & Usage Continuance Intent: A Quantitative Study

Factors Influencing Consumer Acceptance of Mobile Payment during the COVID-19 Pandemic & Usage Continuance Intent: A Quantitative Study

Analisis Perbandingan Optical Character Recognition Google Vision dengan Microsoft Computer Vision pada Pembacaan KTP-el

The Eye: A Light Weight Mobile Application for Visually Challenged People Using Improved YOLOv5l Algorithm

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