Home/Image Processing Projects - Multi-level image representation for large-scale image-based instance retrieval
Image Processing Projects - Multi-level image representation for large-scale image-based instance retrieval
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![](https://www.facebook.com/dialog/feed?app_id=1767574003460647&link=https://pantechelearning.myinstamojo.com/product/image-processing-projects-multi-level-image-&picture=https://storeassets.im-cdn.com/temp/cuploads/ap-south-1%3Afe8af277-4cd5-47f4-b708-2cf09cc993b0/pantechelearning/products/1615981466570PAN-IPM-013--4-.PNG&name=Image Processing Projects - Multi-level image representation for large-scale image-based instance retrieval&caption=undefined&description=<p class="ql-align-justify"><span style="background-color: transparent; color: rgb(0, 0, 0);">In recent years, instance-level-image retrieval has attracted massive attention. Several researchers proposed that the representations learned by convolutional neural network (NN) can be used for image retrieval task. In this study, the authors propose an effective feature encoder to extract robust information from NN. It consists of two main steps: the embedding step and the aggregation step. Moreover, they apply the multi-task loss function to train their model in order to make the training process more effective. Finally, this study proposes a novel representation policy that encodes feature vectors extracted from different layers to capture both local patterns and semantic concepts from deep NN. They call this ‘multi-level-image representation’, which could further improve the performance. The proposed model is helpful to improve the retrieval performance. For the sake of comprehensively evaluating the performance of their approach, they conducted ablation experiments with various convolutional NN architectures</span></p>&redirect_uri=http://www.facebook.com)
Image Processing Projects - Multi-level image representation for large-scale image-based instance retrieval
₹
5,200
₹
6,000
13% off
Exclusive of taxes
Share this
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In recent years, instance-level-image retrieval has attracted massive attention. Several researchers proposed that the representations learned by convolutional neural network (NN) can be used for image retr
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