Multispectral Satellite Image Classification Using Hybrid Convolution Neural Network

2021 ◽  
pp. 541-550
Author(s):  
Krishan Kundu ◽  
Prasun Halder ◽  
Jyotsna Kumar Mandal
2020 ◽  
Vol 167 ◽  
pp. 987-993 ◽  
Author(s):  
Amit Kumar Rai ◽  
Nirupama Mandal ◽  
Akansha Singh ◽  
Krishna Kant Singh

Author(s):  
Jaya Gupta ◽  
◽  
Sunil Pathak ◽  
Gireesh Kumar

Image classification is critical and significant research problems in computer vision applications such as facial expression classification, satellite image classification, and plant classification based on images. Here in the paper, the image classification model is applied for identifying the display of daunting pictures on the internet. The proposed model uses Convolution neural network to identify these images and filter them through different blocks of the network, so that it can be classified accurately. The model will work as an extension to the web browser and will work on all websites when activated. The extension will be blurring the images and deactivating the links on web pages. This means that it will scan the entire web page and find all the daunting images present on that page. Then we will blur those images before they are loaded and the children could see them. Keywords— Activation Function, CNN, Images Classification , Optimizers, VGG-19


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