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Proceedings ArticleDOI

A Durian Variety Identifier Using Canny Edge and CNN

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TLDR
In this paper, a Raspberry Pi was used to implement image processing algorithms and to create a portable device to identify the fruit's variety, which can be used in today's modern technology like in medicine, media or the like, and devices are portable for accessibility.
Abstract
Durian belongs to the genus Durio and a native fruit in tropical countries in the regions of Southeast Asia such as Malaysia, Indonesia, Thailand, and the Philippines. Durian can be easily recognized by its spiky husk and pungent aroma. There are plenty of varieties of Durian which are hard to differentiate by someone who is even an expert of the said fruit. This study is conducted to utilize Raspberry Pi. It will be used to implement image processing algorithms and to create a portable device to identify the fruit’s variety. Image Processing has been used in today’s modern technology like in medicine, media, or the like, and devices are portable for accessibility. The researcher has considered the usefulness of this study and to further understand and acquire useful information of the portable device that will be created to identify Durian variants. Due to the multiple numbers of Durian varieties, the researcher has to determine 6 variants. As the study focused on the unknown variant, the researcher will use a guide on the datasets that will be needed for the training and testing phase of the software. The whole device would then be inspected and would document the accuracy of each variant. The data that the researcher will need to determine the quality and the accuracy of the software, further training and more testing will be needed to get the required acceptable accuracy percentage.

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Citations
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Bacterial Leaf Blight Identification of Rice Fields Using Tiny YOLOv3

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Identification of Macro-Nutrient Deficiency in Onion Leaves (Allium cepa L.) Using Convolutional Neural Network (CNN)

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References
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Journal ArticleDOI

Static Hand Gesture Recognition Using Artificial Neural Network

TL;DR: A new method supporting hand gesture recognition in the static form, using artificial neural network is proposed, which has been tested with high accuracy (98%) and is promising.
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Geometric Analysis of Skin Lesion for Skin Cancer Using Image Processing

TL;DR: Geometric features of the skin lesion are extracted following the asymmetry, border, and diameter parameters of the ABCD-Rule of Dermoscopy using k-Nearest Neighbors algorithm for classification.
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Plant Identification by Image Processing of Leaf Veins

TL;DR: This study focuses on building a portable device capable of plant identification by image processing of leaf veins using Raspberry pi and the devise that the study will develop can help professionals in the field of Botany and Biology.
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Durian Types Recognition Using Deep Learning Techniques

TL;DR: The aim of this research work is to develop an effective method to classify the various cultivars of Durio zibethinus based on the crop's visual features via the application of CNN to improve the accuracy and speed of the cultivars recognition.
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FPGA-Based Plant Identification Through Leaf Veins

TL;DR: This study is focusing on plant identification with the use of field-programmable gate array (FPGA) device Altera DE1-SoC Cyclone V platform using the convolutional neural network (CNN) based on the technology called OpenCL.
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