2020
DOI: 10.11591/ijece.v10i6.pp6531-6540
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An effective identification of crop diseases using faster region based convolutional neural network and expert systems

Abstract: 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 b… Show more

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Cited by 25 publications
(20 citation statements)
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“…Sensor devices are used to monitor the control and read the information to monitor the environments of planting. The sensors that are commonly used in agriculture consisted of temperature sensor [26], [28], [29] water level sensor [23]- [26], [28], [29], humidity sensor [26], [29], soil moisture sensors [29], light sensor, [26], [29] and pressure sensor [21], [26], [29]. The sensor devices are related with hardware control devices which are a part in physical layer.…”
Section: Sensor Devicesmentioning
confidence: 99%
See 1 more Smart Citation
“…Sensor devices are used to monitor the control and read the information to monitor the environments of planting. The sensors that are commonly used in agriculture consisted of temperature sensor [26], [28], [29] water level sensor [23]- [26], [28], [29], humidity sensor [26], [29], soil moisture sensors [29], light sensor, [26], [29] and pressure sensor [21], [26], [29]. The sensor devices are related with hardware control devices which are a part in physical layer.…”
Section: Sensor Devicesmentioning
confidence: 99%
“…The representation of information from these devices is done by using web browser [21]- [22], [28] or mobile application [23], [26], [28], [29]. The web application is responsible for supporting a responsive design.…”
Section: The Representation Of Informationmentioning
confidence: 99%
“…In [44], Deep Residual Neural Network-based algorithm is used for detecting multiple plant diseases which achieved a balanced accuracy of 0.87 under challenging testing. In [45], faster region-based convolutional neural network is used to classify images within images within 0.2 seconds. In [46], a Convolutional Neural Network based approach is proposed for mapping crop types.…”
Section: Related Workmentioning
confidence: 99%
“…There are three main detectors: Faster Region-Based Convolutional Neural Network (Faster R-CNN), Region-Based Fully Convolutional Network (R-FCN), and Single-Shot Multi-Shot Box Detector (SSD). The system can effectively identify different types of diseases with the ability to handle complex scenarios from the plant's area (Hari et al, 2019;Chandana et al, 2020).…”
Section: Introductionmentioning
confidence: 99%