Adventures in data analysis: A systematic review of Deep Learning techniques for pattern recognition in cyber-physical-social systems

Z Amiri, A Heidari, NJ Navimipour, M Unal… - Multimedia Tools and …, 2024 - Springer
Abstract Machine Learning (ML) and Deep Learning (DL) have achieved high success in
many textual, auditory, medical imaging, and visual recognition patterns. Concerning the …

A topic modeling comparison between lda, nmf, top2vec, and bertopic to demystify twitter posts

R Egger, J Yu - Frontiers in sociology, 2022 - frontiersin.org
The richness of social media data has opened a new avenue for social science research to
gain insights into human behaviors and experiences. In particular, emerging data-driven …

Recent advances in deep learning models: a systematic literature review

R Malhotra, P Singh - Multimedia Tools and Applications, 2023 - Springer
In recent years, deep learning has evolved as a rapidly growing and stimulating field of
machine learning and has redefined state-of-the-art performances in a variety of …

Smart manufacturing systems: a futuristics roadmap towards application of industry 4.0 technologies

A Singh, G Madaan, S Hr, A Kumar - International Journal of …, 2023 - Taylor & Francis
The information and communication technology (ICT) field is rapidly advancing and has
developed several disrupting technologies, including artificial intelligence, virtual reality, big …

IoT-based bee swarm activity acoustic classification using deep neural networks

A Zgank - Sensors, 2021 - mdpi.com
Animal activity acoustic monitoring is becoming one of the necessary tools in agriculture,
including beekeeping. It can assist in the control of beehives in remote locations. It is …

Analyzing the quality of business English teaching using multimedia data mining

Y Xin - Mobile Information Systems, 2021 - Wiley Online Library
Data continually act as a substantial role in business and industry for its daily activities to
smoothly functional. The data volume is growing with the passage of time and rising of …

[HTML][HTML] Using multi-criteria decision-making and machine learning for football player selection and performance prediction: A systematic review

A Ati, P Bouchet, RB Jeddou - Data Science and Management, 2023 - Elsevier
Evaluating and selecting players to suit football clubs and decision-makers (coaches,
managers, technical, and medical staff) is a difficult process from a managerial-financial and …

Empowering deep learning based organizational decision making: A Survey

M Mohamed - Sustainable Machine Intelligence Journal, 2023 - sciencesforce.com
The advent of deep learning has revolutionized the landscape of organizational decision-
making by offering powerful tools for data analysis and prediction. In this comprehensive …

Task-oriented ml/dl library recommendation based on a knowledge graph

M Liu, C Zhao, X Peng, S Yu, H Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
AI applications often use ML/DL (Machine Learning/Deep Learning) models to implement
specific AI tasks. As application developers usually are not AI experts, they often choose to …

New distributed-topsis approach for multi-criteria decision-making problems in a big data context

L Lamrini, MC Abounaima, M Talibi Alaoui - Journal of Big Data, 2023 - Springer
Nowadays, the online environment is extra information-rich and allows companies to offer
and receive more and more options and opportunities in multiple areas. Thus, decision …