Numerous class labels associated with each data instance is the main feature of any multi-
label classification (MLC) problem. Correct prediction of class labels related to any test data …

Multilabel classification (MLC) learning, which is widely applied in real‐world applications, is
a very important problem in machine learning. Some studies show that a clustering‐based …

The area of an image multi-label classification is increase continuously in last few years, in
machine learning and computer vision. Multi-label classification has attracted significant …

In any Multi label classification problem, each instance is associated with multiple class
labels. In this paper, we aim to predict the class labels of the test data accurately, using an …

At times, we must snap pictures in the sand and dusty environments. The obtained images
exhibit low visibility and color deviation properties, which have a significant negative impact …

Multi-label classification is a unique challenge in machine learning designed for two targets
with each containing one or multiple classes. This problem can be resolved using several …

The use of mel-frequency cepstral coeffcients (MFCCs) has proven to be a powerful tool in
music and voice recognition, and sound recognition in general. This paper is focused on …

Everyone today can access the streaming content on their mobile phones, laptops very
easily and video has been a very important and popular content on the internet. Nowadays …

Single-label classification models have been widely used for human-face classification. In
this paper, we present a multi-label classification approach for human-face classification …