Recent image retrieval techniques are focusing on multiple image features for the efficient
image retrieval. It has been an inevitable requirement to fetch the images from a variety of …

The study comprehensively reviews previous research work in the domain of 'Organizational
Virtuousness'(OV) using bibliometric and content analysis. It aims to provide insights into …

This research aims to investigate the relationships between work environment, work
engagement, employee well-being, and performance at PT. DBN. The study employs a …

Intelligent and efficient image retrieval from versatile image datasets is an inevitable
requirement of the current era. Primitive image signatures are vital to reflect the visual …

This article presents symmetry of sampling, scoring, scaling, filtering and suppression over
deep convolutional neural networks in combination with a novel content-based image …

Content Based Image Retrieval (CBIR) is a challenging ground to retrieve the images based
on feature description and extraction. Salient image features are the potential candidates to …

Texture is a significant component used for several applications in content-based image
retrieval. Any texture classification method aims to map an anonymously textured input …

Clustering the images is generally based on the image's visual features. Selection of
relevant features is the most essential task. A clustering approach based on the bundled …

Medical images are growing dramatically both in quantity and application in the data era
and the emerging Big Data problem. Searching and finding the proper medical image …

This article presents a novel hybrid learning approach that combines hand-crafted features,
including Scale-Invariant Feature Transform (SIFT) and Haralick texture, with deep-activated …