Implementation of face and eye detection on DM6437 board using simulink model

Vijayalaxmi, B.; Sekaran, Kaushik; Neelima, N.; Chandana, P.; Meqdad, Maytham N.; Kadry, Seifedine

doi:10.11591/eei.v9i2.1703

Cited by 3 publications

(2 citation statements)

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“…The experimentation is carried out on the maize crop which has a greater number of classifications of infections and diseases [21][22][23][24][25] due to bacteria, fungus, pests, and climatic conditions. The results of rot identification using faster regional convolutional neural network (R-CNN) are shown in Figure 7…”

Section: Resultsmentioning

confidence: 99%

An effective identification of crop diseases using faster region based convolutional neural network and expert systems

Chandana

Ghantasala²,

Jeny

et al. 2020

IJECE

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The majority of research Study is moving towards cognitive computing, ubiquitous computing, internet of things (IoT) which focus on some of the real time applications like smart cities, smart agriculture, wearable smart devices. The objective of the research in this paper is to integrate the image processing strategies to the smart agriculture techniques to help the farmers to use the latest innovations of technology in order to resolve the issues of crops like infections or diseases to their crops which may be due to bugs or due to climatic conditions or may be due to soil consistency. As IoT is playing a crucial role in smart agriculture, the concept of infection recognition using object recognition the image processing strategy can help out the farmers greatly without making them to learn much about the technology and also helps them to sort out the issues with respect to crop. In this paper, an attempt of integrating kissan application with expert systems and image processing is made in order to help the farmers to have an immediate solution for the problem identified in a crop.

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Section: Resultsmentioning

confidence: 99%

An effective identification of crop diseases using faster region based convolutional neural network and expert systems

Chandana

Ghantasala²,

Jeny

et al. 2020

IJECE

Self Cite

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“…In addition to theoretical research, research implementing eye-tracking technology has been done before [13]- [15]. In their study, Zhang et al [16] proposed an eye-tracking-based control system for natural human-computer interaction to provide a more natural and convenient communication mechanism.…”

Section: Introductionmentioning

confidence: 99%

System interactive reader using eye-tracker technology in ebook reader

Sujaini,

Safriadi,

Khairiyah

2024

Bulletin EEI

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Interest in using ebooks by the academic community is very high. Still, there is a problem when readers are reading through screens, tend to read fast, only scan the necessary parts, and don't focus on paying attention to the content they read, so this reduces the quality of reading because readers don't study the overall meaning of the sentence. Hence, this research aims to build an interactive reader system by integrating eye tracker technology with a webcam which is expected to solve the problem of decreasing the quality of reading through the screen by helping readers stay focused on their reading and providing an interactive system that makes it easier for readers to control the computer while reading. This research adopts the waterfall method and is divided into six stages. The system is designed using class diagrams, use case diagrams, and activity diagrams. Also, the system is built using the Python language with the Django framework. Then, the interactive reader system was tested using black box testing and usability testing methods. Based on the test results, it is shown that the interactive reader system that was built can help improve the quality and concentration when reading activities take place.

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