A Survey of incremental deep learning for defect detection in manufacturing

R Mohandas, M Southern, E O'Connell… - Big Data and Cognitive …, 2024 - mdpi.com
Deep learning based visual cognition has greatly improved the accuracy of defect detection,
reducing processing times and increasing product throughput across a variety of …

Continual Learning for Smart City: A Survey

L Yang, Z Luo, S Zhang, F Teng, T Li - arXiv preprint arXiv:2404.00983, 2024 - arxiv.org
With the digitization of modern cities, large data volumes and powerful computational
resources facilitate the rapid update of intelligent models deployed in smart cities. Continual …

Development of edge computing and classification using the internet of things with incremental learning for object detection

S Shitharth, H Manoharan, RA Alsowail, A Shankar… - Internet of Things, 2023 - Elsevier
The edge computing method and Internet of Things (IoT), which offers significantly shorter
inactivity intervals, is one of the promising network technologies in today's generation of …

Artificial Intelligence in Virtual Telemedicine Triage: A Respiratory Infection Diagnosis Tool with Electronic Measuring Device

N Villafuerte, S Manzano, P Ayala, MV García - Future Internet, 2023 - mdpi.com
Due to the similarities in symptomatology between COVID-19 and other respiratory
infections, diagnosis of these diseases can be complicated. To address this issue, a web …

Deep learning in public health: Comparative predictive models for COVID-19 case forecasting

MU Tariq, SB Ismail - Plos one, 2024 - journals.plos.org
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates
(UAE) and Malaysia, emphasizing the importance of developing accurate and reliable …

Analysis of the socioeconomic impact due to COVID-19 using a deep clustering approach

Y Quintero, D Ardila, J Aguilar, S Cortes - Applied Soft Computing, 2022 - Elsevier
One of the main problems that countries are currently having is being able to measure the
impact of the pandemic in other areas of society (for example, economic or social). In that …

Analysis of the behavior pattern of energy consumption through online clustering techniques

J Viera, J Aguilar, M Rodríguez-Moreno… - Energies, 2023 - mdpi.com
Analyzing energy consumption is currently of great interest to define efficient energy
management strategies. In particular, studying the evolution of the behavior of the …

Explainability analysis in predictive models based on machine learning techniques on the risk of hospital readmissions

JCL Bedoya, JLA Castro - Health and Technology, 2024 - Springer
Purpose Analyzing the risk of re-hospitalization of patients with chronic diseases allows the
healthcare institutions can deliver accurate preventive care to reduce hospital admissions …

A Study of Data-Driven Methods for Adaptive Forecasting of COVID-19 Cases

C Stylianides, K Malialis, P Kolios - International Conference on Artificial …, 2023 - Springer
Severe acute respiratory disease SARS-CoV-2 has had a profound impact on public health
systems and healthcare emergency response especially with respect to making decisions …

Pandemic infection forecasting through compartmental model and learning-based approaches

M Karapitta, A Kasis, C Stylianides, K Malialis… - arXiv preprint arXiv …, 2024 - arxiv.org
The emergence and spread of deadly pandemics has repeatedly occurred throughout
history, causing widespread infections and loss of life. The rapid spread of pandemics have …