In this paper, we show that clustering the images using the features from the DNN allows more accurate per-cluster classifiers to be learned, which improves the ...

The experiment results show that the proposed FRCM based unsupervised CNN clustering method is better than the standard K-Means, Fuzzy C-Mean, FRCm and also ...

Abstract. Deep clustering aims to promote clustering tasks by combining deep learning and clustering together to learn the clustering-oriented representation, ...

Sep 21, 2021 · The method combines supervised and unsupervised learning algorithms in order to provide qualitative results and performance in real time.

A comprehensive survey on scene recognition is presented. •. Existing scene recognition algorithms are reviewed in the light of feature transformation.

We propose a novel ResNet based transfer learning model utilizing multi-layer feature fusion, taking full advantage of interlayer discriminating features and ...

This repository provides an exhaustive overview of deep learning techniques specifically tailored for satellite and aerial image processing. It covers a range ...

Apr 12, 2021 · This combined method offers unique advantages. Convolutional neural networks enable unsupervised learning of critical feature representations, ...

Apr 28, 2023 · We have shown that unsupervised clustering can be combined with semi-supervised learning to improve overall performance. Our work focuses on ...

In particular, we hypothesized that eye-tracking data would improve the performance of clustering in identifying groups of students with distinct learning.