Classification on Unsupervised Deep Hashing With Pseudo Labels Using Support Vector Machine for Scalable Image Retrieval

Author:

Sharma Rohit,Rai Bipin,Sharma Shubham

Abstract

The content-based image retrieval (CBIR) method operates on the low-level visual features of the user input query object, which makes it difficult for users to formulate the query and also does not provide adequate retrieval results. In the past, image annotation was suggested as the best possible framework for CBIR, which works on automatically signing keywords to images that support image retrieval. The recent successes of deep learning techniques, especially Convolutional Neural Networks (CNN), in solving computer vision applications have inspired me to work on this paper to solve the problem of CBIR using a dataset of annotated images

Publisher

Wasit University

Subject

Industrial and Manufacturing Engineering,Materials Science (miscellaneous),Business and International Management

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unsupervised Deep Hashing via Sample Weighted Contrastive Learning;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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