As the semiconductor industry rapidly develops, wafer defect detection becomes increasingly important, given that wafers are a key raw material[1]. Wafer defects can significantly affect chip reliability and performan...
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The discount factor for reinforcement learning has been constrained to the range [0, 1] to avoid overestimation of state values during training. Although theoretical studies have indicated that discount factors greate...
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Evolutionary Algorithms (EAs) can not handle expensive optimization problems (EOPs) well due to the limited function evaluations in EOPs. To address this challenge, surrogate-assisted evolutionary algorithms (SAEAs) h...
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Modulation classification plays a crucial role in advancing wireless communication research involving the recognition of various radio signals. Most existing neural network-based modulation classification methods rely...
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Pneumonia is a dangerous respiratory disease due to which breathing becomes incredibly difficult and painful;thus,catching it early is *** physicians’time is limited in outdoor situations due to many patients;therefo...
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Pneumonia is a dangerous respiratory disease due to which breathing becomes incredibly difficult and painful;thus,catching it early is *** physicians’time is limited in outdoor situations due to many patients;therefore,automated systems can be a *** input images from the X-ray equipment are also highly unpredictable due to variances in radiologists’***,radiologists require an automated system that can swiftly and accurately detect pneumonic lungs from chest *** medical classifications,deep convolution neural networks are commonly *** research aims to use deep pretrained transfer learning models to accurately categorize CXR images into binary classes,i.e.,Normal and *** MDEV is a proposed novel ensemble approach that concatenates four heterogeneous transfer learning models:Mobile-Net,DenseNet-201,EfficientNet-B0,and VGG-16,which have been finetuned and trained on 5,856 CXR *** evaluation matrices used in this research to contrast different deep transfer learning architectures include precision,accuracy,recall,AUC-roc,and *** model effectively decreases training loss while increasing *** findings conclude that the proposed MDEV model outperformed cutting-edge deep transfer learning models and obtains an overall precision of 92.26%,an accuracy of 92.15%,a recall of 90.90%,an auc-roc score of 90.9%,and f-score of 91.49%with minimal data pre-processing,data augmentation,finetuning and hyperparameter adjustment in classifying Normal and Pneumonia chests.
Metaheuristic algorithms are recommended and frequently used methods for solving optimization problems. Today, it has been adapted to many challenging problems and its successes have been identified. The grey wolf opt...
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Signature verification plays an important role in document authentication. The efficient and robust system is required for forgery detection in documents in the presence of distortion such as rotation, scaling and noi...
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Class Title:Radiological imaging method a comprehensive overview *** GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent ...
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Class Title:Radiological imaging method a comprehensive overview *** GPT paper provides an overview of the different forms of radiological imaging and the potential diagnosis capabilities they offer as well as recent advances in the *** and Methods:This paper provides an overview of conventional radiography digital radiography panoramic radiography computed tomography and cone-beam computed *** recent advances in radiological imaging are discussed such as imaging diagnosis and modern computer-aided diagnosis ***:This paper details the differences between the imaging techniques the benefits of each and the current advances in the field to aid in the diagnosis of medical ***:Radiological imaging is an extremely important tool in modern medicine to assist in medical *** work provides an overview of the types of imaging techniques used the recent advances made and their potential applications.
With the development of deep learning in recent years, code representation learning techniques have become the foundation of many softwareengineering tasks such as program classification [1] and defect detection. Ear...
With the development of deep learning in recent years, code representation learning techniques have become the foundation of many softwareengineering tasks such as program classification [1] and defect detection. Earlier approaches treat the code as token sequences and use CNN, RNN, and the Transformer models to learn code representations.
Video surveillance is widely adopted across various sectors for purposes such as law enforcement, COVID-19 isolation monitoring, and analyzing crowds for potential threats like flash mobs or violence. The vast amount ...
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