Autism Spectrum Disorder(ASD)requires a precise diagnosis in order to be managed and ***-invasive neuroimaging methods are disease markers that can be used to help diagnose *** majority of available techniques in the ...
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Autism Spectrum Disorder(ASD)requires a precise diagnosis in order to be managed and ***-invasive neuroimaging methods are disease markers that can be used to help diagnose *** majority of available techniques in the literature use functional magnetic resonance imaging(fMRI)to detect ASD with a small dataset,resulting in high accuracy but low *** supervised machine learning classification algorithms such as support vector machines function well with unstructured and semi structured data such as text,images,and videos,but their performance and robustness are restricted by the size of the accompanying training *** learning on the other hand creates an artificial neural network that can learn and make intelligent judgments on its own by layering *** takes use of plentiful low-cost computing and many approaches are focused with very big datasets that are concerned with creating far larger and more sophisticated neural *** modelling,also known as Generative Adversarial Networks(GANs),is an unsupervised deep learning task that entails automatically discovering and learning regularities or patterns in input data in order for the model to generate or output new examples that could have been drawn from the original *** are an exciting and rapidly changingfield that delivers on the promise of generative models in terms of their ability to generate realistic examples across a range of problem domains,most notably in image-to-image translation tasks and hasn't been explored much for Autism spectrum disorder prediction in the *** this paper,we present a novel conditional generative adversarial network,or cGAN for short,which is a form of GAN that uses a generator model to conditionally generate *** terms of prediction and accuracy,they outperform the standard *** pro-posed model is 74%more accurate than the traditional methods and takes only around 10 min for training even with a huge dat
The following paper aims at analyzing the role of data science and cybersecurity in strengthening the power systems. Globally, the threats are becoming more complex and frequent where conventional security measures fa...
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Brain-computer interface (BCI) is an emerging technology that receives, processes, and converts brain signals into commands sent to output devices to perform desired tasks. Motor imagery (MI) based on electroencephalo...
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This paper presents an ultra-wideband (UWB) medium power amplifier (MPA) and a broadband high-power power amplifier (HPA) operating at the 5G/6G frequency bands. By using 0.15~\mu \text{m} GaAs pseudomorphic high elec...
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The revolutionary potential of a technology project intended to alter Indian agriculture. Using *** and MongoDB for backend operations and Kotlin Java for frontend development in Android Studio, the suggested applicat...
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The introduction of a pioneering smart solution for public transport is in line with the goals of improving urban mobility and sustainability. This solution offers real-time bus tracking, seat availability and route d...
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With an association of principles created to improve collaboration amidst the operations and development teams, DevOps offers few agile practices. The paper's main goal is to conduct research about how the practic...
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This project aims to solve the problem of securely storing and retrieving luggage in popular public places. There have been various methods that solve the above problem but there is a need for a more simple and effici...
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Breast cancer is a common cause of death among women *** imaging is a valuable diagnostic tool in breast cancer ***,the accuracy of computer-aided diagnosis systems for breast cancer classification is limited due to t...
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Breast cancer is a common cause of death among women *** imaging is a valuable diagnostic tool in breast cancer ***,the accuracy of computer-aided diagnosis systems for breast cancer classification is limited due to the lack of well-annotated *** study proposes a deep learning(DL)-based framework for breast mass classification using ultrasound images,which incorporates a novel data augmentation technique,generative adversarial network(GAN),and transfer learning(TL).Automating early tumor identification and classification in breast cancer diagnosis can save lives by improving the accuracy of diagnoses and reducing the need for invasive ***,the limited availability of wellannotated datasets for ultrasound images of breast cancer has hampered the development of accurate computer-aided diagnosis *** accuracy of breast mass classification using ultrasound images is limited due to the lack of well-annotated *** data augmentation techniques have limitations in applications with strict guidelines,such as medical ***,there is a need to develop a novel data augmentation technique to improve the accuracy of breast mass classification using ultrasound *** proposed framework can be extended to other medical imaging applications,where the availability of well-annotated datasets is *** GAN-based data augmentation technique and TL-based feature extraction can be used to improve the accuracy of classification models in other medical imaging ***,the proposed framework can be used to develop accurate computer-aided diagnosis systems for breast cancer detection in clinical *** proposed framework incorporates a DL-based approach for breast mass classification using ultrasound *** framework includes a GAN-based data augmentation technique and TL for feature *** dataset used for training and testing the model is the breast ultraso
Consuming electricity through Advanced Metering Infrastructure (AMI) has become an irrefutable part of our daily micro-moments. In AMI, electricity fraud is regarded as one of the most significant Nontechnical losses ...
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