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ADS-B Attack Classification using Machine Learning Techniques
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
Automatic Dependent Surveillance Broadcast (ADS-B) is one of the most prominent protocols in Air Traffic Control (ATC). Its key advantages derive from using GPS as a location provider, resulting in better location accuracy ...
Image-based body mass prediction of heifers using deep neural networks
(
Academic Press
, 2021 , Article)
Manual weighing of heifers is time-consuming, labour-intensive, expensive, and can be dangerous and risky for both humans and animals because it requires the animal to be stationary. To overcome this problem, automated ...
Metamorphic relation automation: Rationale, challenges, and solution directions
(
John Wiley and Sons Ltd
, 2022 , Article Review)
Metamorphic testing addresses the issue of the oracle problem by comparing results transformation from multiple test executions. The relationship that governs the output transformation is called metamorphic relation. ...
Deep learning-based multi-task prediction system for plant disease and species detection
(
Elsevier
, 2022 , Article)
The manual prediction of plant species and plant diseases is expensive, time-consuming, and requires expertise that is not always available. Automated approaches, including machine learning and deep learning, are increasingly ...
Product failure detection for production lines using a data-driven model
(
Elsevier
, 2022 , Article)
For a healthy production line, it is essential to ensure a low failure rate of products. Product quality in production lines can be inspected using several techniques at the end of a production process, including a manual ...
Machine Learning-Based Software Defect Prediction for Mobile Applications: A Systematic Literature Review
(
MDPI
, 2022 , Article Review)
Software defect prediction studies aim to predict defect-prone components before the testing stage of the software development process. The main benefit of these prediction models is that more testing resources can be ...
Identification of phantom movements with an ensemble learning approach
(
Elsevier
, 2022 , Article)
Phantom limb pain after amputation is a debilitating condition that negatively affects activities of daily life and the quality of life of amputees. Most amputees are able to control the movement of the missing limb, which ...
A hybrid DNN-LSTM model for detecting phishing URLs
(
Springer Science and Business Media Deutschland GmbH
, 2021 , Article)
Phishing is an attack targeting to imitate the official websites of corporations such as banks, e-commerce, financial institutions, and governmental institutions. Phishing websites aim to access and retrieve users' important ...
Predicting Plasma Vitamin C Using Machine Learning
(
Taylor and Francis Ltd.
, 2022 , Article)
Precision Nutrition makes use of personal information about individuals to produce nutritional recommendations that have more utility than general population level recommendations. In many cases, being able to predict ...
The automation of the development of classification models and improvement of model quality using feature engineering techniques
(
Elsevier
, 2023 , Article)
Recently pipelines of machine learning-based classification models have become important to codify, orchestrate, and automate the workflow to produce an effective machine learning model. In this article, we propose a ...