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Significant strides have been made in artificial neural networks across various fields, necessitating extensive labeled data for effective training. However, the acquisition of such annotated data is both costly and labor-intensive. To address ...

Content-Based Image Retrieval (CBIR) is a method for retrieving images based on their content rather than relying on textual descriptions or tags. Over the last decade, Deep Convolutional Neural Networks (D-CNN) based architectures have gained ...

In this study, a CBIR system for medical radiology images of various anatomical regions and imaging modalities was designed and implemented. Three descriptor-extraction retrieval methods were evaluated: BoVW, HOG, and CNN. Optimal configuration ...

This paper proposes a multi-modal deep learning neural network that combines ResNet and Vision Transformer (ViT) models for a content-based image retrieval (CBIR) system. Experimental results show that this system demonstrates high retrieval accuracy ...

Indoor localization is essential for robotic navigation by using different sensors on board. Specifically, visual localization with a single camera is a great challenge in highly symmetric environments (e.g. offices, hospitals or residences), ...

• A structure with multisensory integration describes symmetrical environments.
• An analytic model is presented for global indoor localization applied to robotics.
• A custom visual detector allows to use characteristic objects as ...

Digital information search archives on the internet and other platforms have been an essential part of our daily lives. With the use of huge amounts of digital images, it is paramount to develop efficient solutions to retrieve images seamlessly. ...

Content-based image retrieval system (CBIR) is a well-known and widely used system for image retrieval. Most of the current CBIR systems are either command-based or specific to applications. However, due to the availability of a good computing ...

Content-Based Image Retrieval (CBIR) leveraging semantic segmentation integrates semantic understanding with image retrieval, enabling users to search for images based on specific objects or regions within them. This paper presents a methodology ...

At present times, the rapid generation of digital images has resulted in a requirement to improve the searching and retrieving process of images from huge databases. The major difficulty is the way of retrieving relevant images from massive ...

Providing visual cues to justify the decisions of deep neural networks contributes significantly to increase their explainability. Typical strategies to provide explanations rely on saliency or attention maps that may not be easy to interpret. ...

The increasing utilization of medical imaging technology with digital storage capabilities has facilitated the compilation of large-scale data repositories. Fast access to image samples with similar appearance to suspected cases in these ...

The traditional Local Binary Pattern (LBP) employs a 3x3 pixel window and examines the intensity differences between the center pixel and nearby neighbourhood pixels. However, LBP excludes the magnitude of difference information entirely, which ...

• An advanced version of darknet-53, Shuffled-Xception-Darknet-53, is proposed.
• A ...

This paper proposes Shuffled-Xception-DarkNet-53, an advanced version of DarkNet-53 for Content-Based Image Retrieval (CBIR). The proposed model introduced the notion of the Shuffled -Xception module, which uses three sets of 1 × 1, 3 ×...

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Content-based image retrieval (CBIR) is an automated process that seeks to retrieve similar/closer images from a large-scale image collection by extracting visual content from the images themselves. In general, CBIR systems consist of two main ...

The traditional annotation-based medical image retrieval faces a problem with competence and precision with the extensive medical image databases. Broad research has been undertaken on Medical image retrieval (MIR) using local, global features of ...

The traditional Local binary pattern (LBP) compares the central pixel with all 8-neighboring pixels in a 3 × 3 pixel window to generate LBP codes. However, its circular structure may result in similar LBP codes for different structural patterns. ...

Explosive growth of multimedia content leads to massive amount of images which are uploaded every day in the cyber world, medical imaging repository, and other areas. Retrieval of image of interest from internet or huge repository of image data ...$\mathrm{}\mathrm{}$$\mathrm{}\mathrm{}$

In the past few years, due to the increased usage of internet, smartphones, sensors and digital cameras, more than a million images are generated and uploaded daily on social media platforms. The massive generation of such multimedia contents has ...

Content-based image retrieval (CBIR) has become one of the trending areas of research in computer vision. In this paper, consonance on hue, saturation, and intensity is used by applying inter-channel voting between them. Diagonally symmetric pattern (DSP) ...

Various modulated techniques of Content-Based Image Retrieval (CBIR) using deep learning provide better search outputs even though they are computationally challenging. These methods can be enhanced further, if the search key can be tagged ...