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Cited by 32 publications
(14 citation statements)
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“…In the agro-industry fast and accurate fruit classification is the highest need. The fruits can be classified into different classes as per their external features like shape, size and color using some computer vision and deep learning techniques [4] , [5] , [6] , [7] , [8] . The FruitNet dataset was created to include Indian fruits along with its quality parameters for those which are highly consumed or exported as per [9] .…”
Section: Data Descriptionmentioning
confidence: 99%
“…In the agro-industry fast and accurate fruit classification is the highest need. The fruits can be classified into different classes as per their external features like shape, size and color using some computer vision and deep learning techniques [4] , [5] , [6] , [7] , [8] . The FruitNet dataset was created to include Indian fruits along with its quality parameters for those which are highly consumed or exported as per [9] .…”
Section: Data Descriptionmentioning
confidence: 99%
“…However, the proposed method has certain limitations and needs to be further explored. This paper only conducts relevant experiments on the pest data set, but in the agricultural field, in addition to pest data, there are many other categories of data that also need to be identified, such as picking classification tasks in fruit farming [30], crop identification tasks, etc. This paper conducts experiments on the task of pest image recognition, but as the data dilemma does not only appear in the recognition task, other tasks also need to solve this problem, such as pest target detection, semantic segmentation [31], etc.…”
Section: Future Workmentioning
confidence: 99%
“…It is a classical artificial neural network framework, which has advantages in processing data like network, such as image and video data. Convolutional neural network uses convolutional mathematics, namely, a mathematical operation of two real variable functions, as shown in the following formula [10][11][12]:…”
Section: Convolutional Neural Network Algorithmmentioning
confidence: 99%