In this study, a convolutional neural network with threshold optimization (CNN-THOP) is
proposed to solve the issue of overlabeling or downlabeling arising during the multilabel …

Generally, traditional convolutional neural networks (CNN) models require a long training
time and output high-dimensional features for content-based remote sensing image retrieval …

The huge amount of active research has been focused on developing the remote sensing
based applications for providing the object classification procedure focusing on the energy …

Benchmark datasets play an important role in evaluating remote sensing image retrieval
(RSIR) methods. The current datasets cover many scene categories, but omit an important …

Deep learning framework aids the researchers in learning different application areas to a
greater extent. Deep learning framework is preferred over machine learning since it helps to …

The advancements in Internet and Web 2.0 technologies resulted in the easier generation
and distribution of digital images. Many images are stored without any form of significant …

This paper presents a novel fuzzy logic based Convolution Neural Network intelligent
classifier for accurate image classification. The proposed approach employs a semantic …

As an important waveform feature, the number of peaks indicates the complexity of the
surface coverage within the laser footprint. At present, the common methods of determining …

High informative feature descriptors always improves the classification process. In order to
classify the earth surface, it is essential to annotate satellite images using itshigh informative …

In recent years, facial image search has been widely used. Although offering considerable
convenience, facial image search also poses a severe threat to people's privacy. How to …