Pervasive AI for IoT applications: A survey on resource-efficient distributed artificial intelligence

E Baccour, N Mhaisen, AA Abdellatif… - … Surveys & Tutorials, 2022 - ieeexplore.ieee.org
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of
Things (IoT) applications and services, spanning from recommendation systems and speech …

Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations

M Yang, Y Huang, C Xu, C Liu, B Dai - Applied Energy, 2025 - Elsevier
Wind power forecasting (WPF) is the crucial technology for power system operation with
large-scale grid-connected wind farms. A large number of related studies have emerged …

[HTML][HTML] Deep transfer learning of additive manufacturing mechanisms across materials in metal-based laser powder bed fusion process

V Pandiyan, R Drissi-Daoudi, S Shevchik… - Journal of Materials …, 2022 - Elsevier
The defective regimes in metal-based Laser Powder Bed Fusion (LPBF) processes can be
minimized by deploying in-situ monitoring strategies comprising Machine learning (ML) …

Artificial intelligence-based drone system for multiclass plant disease detection using an improved efficient convolutional neural network

W Albattah, A Javed, M Nawaz, M Masood… - Frontiers in Plant …, 2022 - frontiersin.org
The role of agricultural development is very important in the economy of a country. However,
the occurrence of several plant diseases is a major hindrance to the growth rate and quality …

A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI

A Bahrami, A Karimian, E Fatemizadeh… - Medical …, 2020 - Wiley Online Library
Purpose Despite the proven utility of multiparametric magnetic resonance imaging (MRI) in
radiation therapy, MRI‐guided radiation treatment planning is limited by the fact that MRI …

Intelligent identification of early esophageal cancer by band-selective hyperspectral imaging

TJ Tsai, A Mukundan, YS Chi, YM Tsao, YK Wang… - Cancers, 2022 - mdpi.com
Simple Summary Early esophageal cancer detection is crucial for patient survival; however,
even skilled endoscopists find it challenging to identify the cancer cells in the early stages. In …

Shallow convolutional neural network for COVID-19 outbreak screening using chest X-rays

H Mukherjee, S Ghosh, A Dhar, SM Obaidullah… - Cognitive …, 2021 - Springer
Among radiological imaging data, Chest X-rays (CXRs) are of great use in observing COVID-
19 manifestations. For mass screening, using CXRs, a computationally efficient AI-driven …

Image captioning by diffusion models: a survey

F Daneshfar, A Bartani, P Lotfi - Engineering Applications of Artificial …, 2024 - Elsevier
Diffusion models are increasingly favored over traditional approaches like generative
adversarial networks (GANs) and auto-regressive transformers due to their remarkable …

An improved residual-based convolutional neural network for very short-term wind power forecasting

C Yildiz, H Acikgoz, D Korkmaz, U Budak - Energy Conversion and …, 2021 - Elsevier
An accurate forecast of wind power is very important in terms of economic dispatch and the
operation of power systems. However, effectively mitigating the risks arising from wind …

Two-step CNN framework for text line recognition in camera-captured images

YS Chernyshova, AV Sheshkus, VV Arlazarov - IEEE Access, 2020 - ieeexplore.ieee.org
In this paper, we introduce an “on the device” text line recognition framework that is
designed for mobile or embedded systems. We consider per-character segmentation as a …