Industry 5.0: A survey on enabling technologies and potential applications

PKR Maddikunta, QV Pham, B Prabadevi… - Journal of industrial …, 2022 - Elsevier
Industry 5.0 is regarded as the next industrial evolution, its objective is to leverage the
creativity of human experts in collaboration with efficient, intelligent and accurate machines …

[Retracted] Deep Neural Networks for Medical Image Segmentation

P Malhotra, S Gupta, D Koundal… - Journal of …, 2022 - Wiley Online Library
Image segmentation is a branch of digital image processing which has numerous
applications in the field of analysis of images, augmented reality, machine vision, and many …

Computational technique based on machine learning and image processing for medical image analysis of breast cancer diagnosis

VDP Jasti, AS Zamani, K Arumugam… - Security and …, 2022 - Wiley Online Library
Breast cancer is the most lethal type of cancer for all women worldwide. At the moment,
there are no effective techniques for preventing or curing breast cancer, as the source of the …

Hand gesture classification using a novel CNN-crow search algorithm

TR Gadekallu, M Alazab, R Kaluri… - Complex & Intelligent …, 2021 - Springer
Human–computer interaction (HCI) and related technologies focus on the implementation of
interactive computational systems. The studies in HCI emphasize on system use, creation of …

Evaluation of neuro images for the diagnosis of Alzheimer's disease using deep learning neural network

M Hamdi, S Bourouis, K Rastislav… - Frontiers in Public …, 2022 - frontiersin.org
Alzheimer's Disease (AD) is a progressive, neurodegenerative brain disease and is an
incurable ailment. No drug exists for AD, but its progression can be delayed if the disorder is …

A novel data augmentation method based on denoising diffusion probabilistic model for fault diagnosis under imbalanced data

X Yang, T Ye, X Yuan, W Zhu, X Mei… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Imbalanced data constitute a significant challenge in intelligent fault diagnosis cases
because they can result in degraded diagnosis accuracy, which can in turn jeopardize the …

Heart failure detection using quantum‐enhanced machine learning and traditional machine learning techniques for internet of artificially intelligent medical things

Y Kumar, A Koul, PS Sisodia, J Shafi… - Wireless …, 2021 - Wiley Online Library
Quantum‐enhanced machine learning plays a vital role in healthcare because of its robust
application concerning current research scenarios, the growth of novel medical trials, patient …

Cross corpus multi-lingual speech emotion recognition using ensemble learning

W Zehra, AR Javed, Z Jalil, HU Khan… - Complex & Intelligent …, 2021 - Springer
Receiving an accurate emotional response from robots has been a challenging task for
researchers for the past few years. With the advancements in technology, robots like service …

Efficient gastrointestinal disease classification using pretrained deep convolutional neural network

M Nouman Noor, M Nazir, SA Khan, OY Song, I Ashraf - Electronics, 2023 - mdpi.com
Gastrointestinal (GI) tract diseases are on the rise in the world. These diseases can have
fatal consequences if not diagnosed in the initial stages. WCE (wireless capsule endoscopy) …

Progress and trends in neurological disorders research based on deep learning

MS Iqbal, MBB Heyat, S Parveen, MAB Hayat… - … Medical Imaging and …, 2024 - Elsevier
In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging,
offering unprecedented opportunities for the diagnosis and treatment of neurological …