A Decade Survey of Content Based Image Retrieval Using Deep Learning

By Shiv Ram Dubey. IEEE transactions on circuits and systems for video technology (Print), 2020

329 citations recorded by the source corpus.

The content based image retrieval aims to find the similar images from a large scale dataset against a query image. Generally, the similarity between the representative features of the query image and dataset images is used to rank the images for retrieval. In early days, various hand designed feature descriptors have been investigated based on the visual cues such as color, texture, shape, etc. that represent the images. However, the deep learning has emerged as a dominating alternative of hand-designed feature engineering from a decade. It learns the features automatically from the data. This paper presents a comprehensive survey of deep learning based developments in the past decade for content based image retrieval. The categorization of existing state-of-the-art methods from different perspectives is also performed for greater understanding of the progress. The taxonomy used in this survey covers different supervision, different networks, different descriptor type and different retrieval type. A performance analysis is also performed using the state-of-the-art methods. The insights are also presented for the benefit of the researchers to observe the progress and to make the best choices. The survey presented in this paper will help in further research progress in image retrieval using deep learning.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/45376c0dbf03efa4184ee3c2639c526cecd9f913

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Bidyut Baran Chaudhuri
2. Satish Kumar Singh
3. Shiv Ram Dubey
4. Atlas Collaboration

In Media Technology

1. Bidyut Baran Chaudhuri
2. Shiv Ram Dubey
3. Atlas Collaboration

Citations in the corpus

• Activation functions in deep learning: A comprehensive survey and benchmark (2021, background): “In recent years, deep learning has shown a tremondous growth to solve the challenging problems such as object detection [1], semantic segmentation [2], person re-identification [3], image retrieval [4], anomaly detection [5], skin disease diagnosis [6], and many more.”