Demonstrating Broadcast Aggregate Keys for Data Sharing in Cloud

Rakshitha, Kosaraju; Rao, Annaluri Sreenivasa; Sagar, Y.; Ramasubbareddy, Somula

doi:10.1007/978-981-15-2043-3_23

Cited by 8 publications

(1 citation statement)

References 3 publications

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“…Artificial neural network helps in getting the data, integrating the features and making the convolutional network more efficient. Since we use many classes of data, we have to use the soft max function [31][32][33][34][35][36][37] (Table 1).…”

Section: Proposed Methodsmentioning

confidence: 99%

Fruit Recognition Using Deep Learning

Reddy

Ramasubbareddy

Saidulu

et al. 2021

Innovations in Computer Science and Engineering

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This paper discusses on the fruits classification for which the data is collected from the dataset called Fruits_360. Using this data, training of a neural network which will identify the fruit. Using the deep learning and image processing concepts form a neural networking system. The proposed work uses convolution neural networks in building the model and also used ResNet to get the results of image classification from deep learning concept. To meet the resource requirement for the proposed work, it uses Google cloud vision API which gives us the required GPU to proceed with the process of analyzing the data from the image and also discussed the in depth of how image classification is done using deep learning concepts. Here, in building a deep learning model, which classifies the given image into any of these nine categories: Apple, Avocado, Banana, Cherry, Cocos, Kiwi, Mango, Orange, Lemon. This model can also be implemented into mobile version.

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