This paper proposed an efficient image retrieval framework by feature-fusion of high-level
features from the improved version of DarkNet-53, named GroupNormalized-Inception …

An innovative image retrieval agenda by concatenating deep learning features from
GoogleNet and low‐level features from HSI and RGB color space is proposed in this article …

In recent days' research, deep learning methods have shown promising performance in
various fields of computer vision, including content-based image retrieval (CBIR). In this …

Abstract Content Based Image Retrieval (CBIR) is the task of finding similar images from a
query one. The state of the art mentions two main methods to solve the retrieval problem:(1) …

Content-based image retrieval (CBIR) is a recent method used to retrieve different types of
images from repositories. The traditional content-based medical image retrieval (CBMIR) …

In today's age, massive image data is generated rapidly. This influx has made labeling
images tedious and, in turn, made it harder to retrieve images through searching algorithms …

Feature extraction, representation, and similarity estimation are all essential to measure the
performance of a content-based image retrieval (CBIR) system, and they have all been …

In tissue characterization and cancer diagnostics, multimodal imaging has emerged as a
powerful technique. Thanks to computational advances, large datasets can be exploited to …

Image retrieval technology has emerged as a popular research area of China's development
of cultural digital image dissemination and creative creation with the growth of the Internet …

立足于深度学习, 提出面向细粒度图像的自适应三元组网络的鲁棒图像检索算法. 首先,
提出的视觉显著性检测方法被用来去除图像噪音, 以便提取图像中目标主体辨识度更高的深度 …