A Survey: How Python Pitches in IT-World

Kumar, Arun; Panda, Supriya P.

doi:10.1109/comitcon.2019.8862251

Cited by 22 publications

(10 citation statements)

References 2 publications

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“…The proposed AOCR post-processing system was implemented using python 3.6 because it has many packages suitable for this task, characterized as an open-source language, can use for any platform operating system and performing various scientific calculations [26]. It was tested using the results of two commercial OCR applications, i2OCR that evaluated by (S, Vijayarani A, Sakila) as better performance among seven other systems [27] and ABBYY FINE READER that provides recognizes text quickly and accurately [28], on several images of Islamic book pages that had errors due to the poor quality of the images.…”

Section: Resultsmentioning

confidence: 99%

Corpus-based technique for improving Arabic OCR system

Aliwy

Al-Sadawi

2021

IJEECS

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<p><span>An optical character recognition (OCR) refers to a process of converting the text document images into editable and searchable text. OCR process poses several challenges in particular in the Arabic language due to it has caused a high percentage of errors. In this paper, a method, to improve the outputs of the Arabic Optical character recognition (AOCR) Systems is suggested based on a statistical language model built from the available huge corpora. This method includes detecting and correcting non-word and real words error according to the context of the word in the sentence. The results show that the percentage of improvement in the results is up to (98%) as a new accuracy for AOCR output. </span></p>

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Section: Resultsmentioning

confidence: 99%

Corpus-based technique for improving Arabic OCR system

Aliwy

Al-Sadawi

2021

IJEECS

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“…A linguagem Python foi escolhida neste trabalho por ser uma linguagem de código aberto, de alto nível e muito utilizada. Além disso, possibilita que mesmo pessoas sem conhecimento em programação possam entender ou até mesmo testar os scripts (Kumar and Panda, 2019). Existem diversas interfaces de desenvolvimento e editores de código para linguagem Python.…”

Section: Resultsunclassified

Controle remoto de ferramentas de aperto usando o Open Protocol

Makoski

Silva

Assef

2020

Anais Do Congresso Brasileiro De Automática 2020

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O aumento da demanda por produtos exclusivos com alta qualidade e baixo custo tem feito as empresas inovarem nos processos produtivos. Na industria automotiva não ée diferente. No setor industrial há diversos tipos de ferramentas de fabricação, montagem e aperto. Controlar e rastrear esses parâmetros garante uma produção eficiente, adequada aos programas de qualidade e seguranca exigidos pela lei e pelo mercado consumidor. Este artigo visa especificamente resumir, baseado no manual do fabricante, e testar, através de um conjunto de códigos desenvolvidos em linguagem de programação Python, uma maneira a controlar remotamente ferramentas de aperto que utilizam o protocolo de comunicação Open Protocol, desenvolvido pela empresa Atlas Copco. Para os testes de avaliação dos comandos de torque e ângulo foram utilizados dois controladores de marcar diferentes e os resultados entre as interfaces desenvolvidas de usuário e Web mostraram perfeita concordância. O modelo proposto poderáa ser explorado por estudantes e profissionais para otimizar recursos e desempenho na área de manufatura no âmbito da indústria 4.0, também conhecida como fábrica inteligente.

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“…Saikia et al (2014) proposed a sensor network to monitor the relative humidity and temperature of tea during fermentation. Also, Uehara and Ohtake (2019) developed an IoT-based system for monitoring the temperature and humidity of tea during processing, while Kumar (2017) proposed an IoT-based system to monitor the temperature and humidity of tea during fermentation. The proposed works have been deployed in a tea factory to monitor temperature and humidity during tea processing.…”

Section: Related Workmentioning

confidence: 99%

An internet of things (IoT)-based optimum tea fermentation detection model using convolutional neural networks (CNNs) and majority voting techniques

Kimutai

Ngenzi

Ngoga

et al. 2021

J. Sens. Sens. Syst.

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Abstract. Tea (Camellia sinensis) is one of the most consumed drinks across the world. Based on processing techniques, there are more than 15 000 categories of tea, but the main categories include yellow tea, Oolong tea, Illex tea, black tea, matcha tea, green tea, and sencha tea, among others. Black tea is the most popular among the categories worldwide. During black tea processing, the following stages occur: plucking, withering, cutting, tearing, curling, fermentation, drying, and sorting. Although all these stages affect the quality of the processed tea, fermentation is the most vital as it directly defines the quality. Fermentation is a time-bound process, and its optimum is currently manually detected by tea tasters monitoring colour change, smelling the tea, and tasting the tea as fermentation progresses. This paper explores the use of the internet of things (IoT), deep convolutional neural networks, and image processing with majority voting techniques in detecting the optimum fermentation of black tea. The prototype was made up of Raspberry Pi 3 models with a Pi camera to take real-time images of tea as fermentation progresses. We deployed the prototype in the Sisibo Tea Factory for training, validation, and evaluation. When the deep learner was evaluated on offline images, it had a perfect precision and accuracy of 1.0 each. The deep learner recorded the highest precision and accuracy of 0.9589 and 0.8646, respectively, when evaluated on real-time images. Additionally, the deep learner recorded an average precision and accuracy of 0.9737 and 0.8953, respectively, when a majority voting technique was applied in decision-making. From the results, it is evident that the prototype can be used to monitor the fermentation of various categories of tea that undergo fermentation, including Oolong and black tea, among others. Additionally, the prototype can also be scaled up by retraining it for use in monitoring the fermentation of other crops, including coffee and cocoa.

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A Survey: How Python Pitches in IT-World

Cited by 22 publications

References 2 publications

Corpus-based technique for improving Arabic OCR system

Corpus-based technique for improving Arabic OCR system

Controle remoto de ferramentas de aperto usando o Open Protocol

An internet of things (IoT)-based optimum tea fermentation detection model using convolutional neural networks (CNNs) and majority voting techniques

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