Machine Learning and Knowledge Extraction, Volume 4, Issue 3

This paper uses various machine learning methods which explore the combination of multiple sensors for quality improvement. It is known that a reliable occupancy estimation can help in many different cases and applications. For the containment of the...

Factorizable joint shift (FJS) was recently proposed as a type of dataset shift for which the complete characteristics can be estimated from feature data observations on the test dataset by a method called Joint Importance Aligning. For the multinomi...

There is a need to predict occupational injuries in South African National Parks for the purpose of implementing targeted interventions or preventive measures. Machine-learning models have the capability of predicting injuries such that the employees...

Nowadays, underwater video systems are largely used by marine ecologists to study the biodiversity in underwater environments. These systems are non-destructive, do not perturb the environment and generate a large amount of visual data usable at any...

Due to the requirement of video surveillance, machine learning-based single image deraining has become a research hotspot in recent years. In order to efficiently obtain rain removal images that contain more detailed information, this paper proposed...

Machine learning represents a milestone in data-driven research, including material informatics, robotics, and computer-aided drug discovery. With the continuously growing virtual and synthetically available chemical space, efficient and robust quant...

The implementation of data mining has become very popular in many fields recently, including in the petroleum industry. It is widely used to help in decision-making processes in order to minimize oil losses during operations. One of the major causes...

The purpose of this study is to provide an efficient method for the selection of input–output indicators in the data envelopment analysis (DEA) approach, in order to improve the discriminatory power of the DEA method in the evaluation process a...

Training deep learning models requires having the right data for the problem and understanding both your data and the models’ performance on that data. Training deep learning models is difficult when data are limited, so in this paper, we seek...

The COVID-19 pandemic has impacted daily lives around the globe. Since 2019, the amount of literature focusing on COVID-19 has risen exponentially. However, it is almost impossible for humans to read all of the studies and classify them. This article...