Nanoengineered graphene metasurface surface plasmon resonance sensor for precise hemoglobin detection with AI-assisted performance prediction
The development of highly sensitive and reliable biosensors for hemoglobin detection is
crucial for various medical and diagnostic applications. Hemoglobin, a vital protein in red …
crucial for various medical and diagnostic applications. Hemoglobin, a vital protein in red …
State-of-art technologies, challenges, and emerging trends of computer vision in dental images
J Priya, SKS Raja, SU Kiruthika - Computers in Biology and Medicine, 2024 - Elsevier
Computer vision falls under the broad umbrella of artificial intelligence that mimics human
vision and plays a vital role in dental imaging. Dental practitioners visualize and interpret …
vision and plays a vital role in dental imaging. Dental practitioners visualize and interpret …
State-of-the-art in 1D Convolutional Neural Networks: A survey
Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …
most common approach being the Convolutional Neural Network (CNN). Through CNN …
A comprehensive review on the advancement of high-dimensional neural networks in quaternionic domain with relevant applications
The neurocomputing communities have focused much interest on quaternionic-valued
neural networks (QVNNs) due to the natural extension in quaternionic signals, learning of …
neural networks (QVNNs) due to the natural extension in quaternionic signals, learning of …
Deep learning techniques for OFDM systems
M Meenalakshmi, S Chaturvedi… - IETE journal of …, 2023 - Taylor & Francis
Orthogonal frequency division multiplexing (OFDM) is a popular multicarrier technique in
communication system owing to its robustness against multipath fading and less complexity …
communication system owing to its robustness against multipath fading and less complexity …
An application of CNN to classify barchan dunes into asymmetry classes
Barchan morphometric data have been used as proxies of meteorological and topographical
data in environments where this data is lacking (such as other planetary bodies), gaining …
data in environments where this data is lacking (such as other planetary bodies), gaining …
A fuzzy evaluation approach to determine superiority of deep learning network system in terms of recognition capability: case study of lung cancer imaging
TC Chang - Annals of Operations Research, 2023 - Springer
Artificial intelligence (AI) assists in decision-making across various fields and industries.
Diverse market needs have prompted the rapid evolution of AI learning algorithms. Deep …
Diverse market needs have prompted the rapid evolution of AI learning algorithms. Deep …
Instance segmentation of on-line wear debris using deep convolutional neural network with transfer learning
J Li, M Chen - Industrial Lubrication and Tribology, 2024 - emerald.com
Purpose This study aims to apply deep convolutional neural network Mask-R-CNN algorithm
based on transfer learning to realize the segmentation of online wear fragments …
based on transfer learning to realize the segmentation of online wear fragments …
Lightweight Differential Frameworks for CSI Feedback in Time-Varying Massive MIMO Systems
Y Zhang, X Zhang, Y Liu - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
Channel state information (CSI) is vital for massive multiple-input multiple-output (MIMO)
systems to provide high channel capacity and energy efficiency. However, the massive …
systems to provide high channel capacity and energy efficiency. However, the massive …
Generative AI-based Land Cover Classification via Federated Learning CNNs: Sustainable Insights from UAV Imagery
O Jockusch, MZ Hossain, A Imteaj… - 2024 IEEE Conference …, 2024 - ieeexplore.ieee.org
This paper introduces a novel approach method for decentralized land cover and land use
classification, utilizing federated learning in conjunction with Convolutional Neural Networks …
classification, utilizing federated learning in conjunction with Convolutional Neural Networks …