Abstract: Brain tumors are now the second most common serious consequence worldwide, after cardiovascular disorders. Early detection and treatment of brain cancers save millions of lives worldwide.
Abstract: Ultrasound detection can promptly identify partial discharge (PD) faults inside power transformer by using fiber-optic Fabry-Perot (F-P) array sensors. This paper presents a new design ...
Abstract: Currently, the rapid development of the aviation industry has made the safety of the airport becomes more and more important. The most important part of this is the capability of ...
Abstract: Intelligent fault diagnosis using AI models is an evolving engineering technique in the manufacturing sector. It detects anomalies in machinery and improves productivity, safety, efficiency, ...
Abstract: Image steganography conceals secret data within a cover image to generate a new image (stego image) in a manner that makes the secret data undetectable. The main problem in image ...
Abstract: The main objective of proposed research is to employ DL (Deep Learning) models to predict User-to-Root (U2R) attack using CNN (Convolution Neural Network) Alexnet. In this study, the dataset ...
Online grocery delivery service Instacart used AI to charge different prices for the same item, up to 20% more for different shoppers, a new report says. An investigation from Consumer Reports and ...
Abstract: Accurate and early disease detection from chest X-ray (CX-ray) images is crucial for effective clinical decision-making. This study proposes a novel Ensemble Hybrid Recurrent ...
Abstract: This article proposes a distance measurement error suppression algorithm based on convolutional neural network (CNN)-Transformer-Bidirectional long short ...
Abstract: Cryptographic techniques are reviewed in this literature review, with particular attention paid to their applicability, importance, contributions, and field strengths. These algorithms ...
Abstract: Convolution Neural Network (CNN) algorithms have demonstrated notable capability in effectively analyzing human body image datasets obtained from MRI or CT with sufficient efficiency to ...
Abstract: This paper presents an experiment and results of the modified CNN algorithm, it was developed by combining a compact 1D convolution neural network with a tuned signal filter (low-pass filter ...
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