A survey on the role of Internet of Things for adopting and promoting Agriculture 4.0
There is a rapid increase in the adoption of emerging technologies like the Internet of Things
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …
(IoT), Unmanned Aerial Vehicles (UAV), Internet of Underground Things (IoUT), Data …
The use of machine learning algorithms in recommender systems: A systematic review
I Portugal, P Alencar, D Cowan - Expert Systems with Applications, 2018 - Elsevier
Recommender systems use algorithms to provide users with product or service
recommendations. Recently, these systems have been using machine learning algorithms …
recommendations. Recently, these systems have been using machine learning algorithms …
Csrnet: Dilated convolutional neural networks for understanding the highly congested scenes
We propose a network for Congested Scene Recognition called CSRNet to provide a data-
driven and deep learning method that can understand highly congested scenes and perform …
driven and deep learning method that can understand highly congested scenes and perform …
Hybrid deep learning-based models for crop yield prediction
A Oikonomidis, C Catal, A Kassahun - Applied artificial intelligence, 2022 - Taylor & Francis
Predicting crop yield is a complex task since it depends on multiple factors. Although many
models have been developed so far in the literature, the performance of current models is …
models have been developed so far in the literature, the performance of current models is …
Potato yield prediction using machine learning techniques and sentinel 2 data
Traditional potato growth models evidence certain limitations, such as the cost of obtaining
the input data required to run the models, the lack of spatial information in some instances …
the input data required to run the models, the lack of spatial information in some instances …
The impact of entrepreneurship orientation on project performance: A machine learning approach
Recent studies in project management have shown the important role of entrepreneurship
orientation of the individuals in project performance. Although identifying the role of …
orientation of the individuals in project performance. Although identifying the role of …
Teaching Machine Learning as Part of Agile Software Engineering
S Chenoweth, PK Linos - IEEE Transactions on Education, 2023 - ieeexplore.ieee.org
Contribution: A novel undergraduate course design at the intersection of software
engineering (SE) and machine learning (ML) based on industry-reported challenges …
engineering (SE) and machine learning (ML) based on industry-reported challenges …
Software defect prediction using relational association rule mining
This paper focuses on the problem of defect prediction, a problem of major importance
during software maintenance and evolution. It is essential for software developers to identify …
during software maintenance and evolution. It is essential for software developers to identify …
A novel approach for software defect prediction through hybridizing gradual relational association rules with artificial neural networks
The growing complexity of software projects requires increasing consideration of their
analysis and testing. Identifying defective software entities is essential for software quality …
analysis and testing. Identifying defective software entities is essential for software quality …
Data mining algorithms for smart cities: A bibliometric analysis
A Kousis, C Tjortjis - Algorithms, 2021 - mdpi.com
Smart cities connect people and places using innovative technologies such as Data Mining
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …
(DM), Machine Learning (ML), big data, and the Internet of Things (IoT). This paper presents …