Modern information technology is driving the rapid development of the information and automation industry through the combination of computertechnology, communication technology, and control technology. Inspired by n...
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Numerous deep learning (DL) models based on convolutional neural network (CNN) have been developed for image classification. Though the CNN models attained outstanding performance, its architecture contains certain li...
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Numerous morphological and histological characteristics of brain tumors make diagnosis and treatment very challenging. Traditional diagnosis methods often depend on the analysis of medical images, which can lead to un...
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Ransomware, a form of malicious software, encrypts victim data and renders it inaccessible until a ransom is paid. Different ransomware variants employ various tactics to avoid detection during their attacks. Understa...
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Introduction: Pathologists are majorly concerned with detecting the diseases and helping the patients in their healthcare and well-being. The present method used by pathologists for this purpose is manually viewing th...
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Introduction: Pathologists are majorly concerned with detecting the diseases and helping the patients in their healthcare and well-being. The present method used by pathologists for this purpose is manually viewing the slides using a microscope and other instruments. However, this method has a number of limitations such as there is no standard way of diagnosis, there are certain chances of human errors and besides, it burdenizes the laboratory personnel to diagnose a large number of slides on a daily basis. Methods: The slide viewing method is widely used and converted into digital form to produce high resolution images. This enables the area of deep learning and machine learning to get an insight into this field of medical sciences. In the present study, a neural based network has been proposed for classification of blood cells images into various categories. When an input image is passed through the proposed architecture and all the hyper parameters and dropout ratio values are applied in accordance with the proposed algorithm, then the model classifies the blood images with an accuracy of 95.24%. Result: After training the models on 20 epochs. The plots of training accuracy, testing accuracy and corresponding training loss, and testing loss for the proposed model is plotted using matplotlib and trends. Discussion: The performance of the proposed model is better than the existing standard architectures and other works done by various researchers. Thus, the proposed model enables the development of pathological system which will reduce human errors and daily load on laboratory personnel. . This can also in turn help the pathologists in carrying out their work more efficiently and effectively. Conclusion: In the present study, a neural based network has been proposed for classification of blood cells images into various categories. These categories have significance in the medical sciences. When input image is passed through the proposed architecture and all the hyp
Antimicrobial resistance (AMR) is one of the significant problems in the health sector and requires resources to create and develop accurate forecasting systems capable of recognizing resistant microbes and their trea...
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Cybercrime has increased considerably in recent times by creating new methods of stealing,changing,and destroying data in daily *** Docu-ment Format(PDF)has been traditionally utilized as a popular way of spreading **...
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Cybercrime has increased considerably in recent times by creating new methods of stealing,changing,and destroying data in daily *** Docu-ment Format(PDF)has been traditionally utilized as a popular way of spreading *** recent advances of machine learning(ML)and deep learning(DL)models are utilized to detect and classify *** this motivation,this study focuses on the design of mayfly optimization with a deep belief network for PDF malware detection and classification(MFODBN-MDC)*** major intention of the MFODBN-MDC technique is for identifying and classify-ing the presence of malware exist in the *** proposed MFODBN-MDC method derives a new MFO algorithm for the optimal selection of feature *** addition,Adamax optimizer with the DBN model is used for PDF malware detection and classifi*** design of the MFO algorithm to select features and Adamax based hyperparameter tuning for PDF malware detection and classi-fication demonstrates the novelty of the *** demonstrating the improved outcomes of the MFODBN-MDC model,a wide range of simulations are exe-cuted,and the results are assessed in various *** comparison study high-lighted the enhanced outcomes of the MFODBN-MDC model over the existing techniques with maximum precision,recall,and F1 score of 97.42%,97.33%,and 97.33%,respectively.
Robotic systems that can be operated remotely are becoming more and more common in a variety of industries, including construction, disaster relief, space exploration, and industrial applications. Teleoperation, howev...
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Relative overgeneralization (RO) occurs in cooperative multi-agent learning tasks when agents converge towards a suboptimal joint policy due to overfitting to suboptimal behaviors of other *** methods have been propos...
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Relative overgeneralization (RO) occurs in cooperative multi-agent learning tasks when agents converge towards a suboptimal joint policy due to overfitting to suboptimal behaviors of other *** methods have been proposed for addressing RO in multi-agent policy gradient (MAPG) methods although these methods produce state-of-the-art *** address this gap, we propose a general, yet simple, framework to enable optimistic updates in MAPG methods that alleviate the RO *** approach involves clipping the advantage to eliminate negative values, thereby facilitating optimistic updates in *** optimism prevents individual agents from quickly converging to a local ***, we provide a formal analysis to show that the proposed method retains optimality at a fixed *** extensive evaluations on a diverse set of tasks including the Multi-agent MuJoCo and Overcooked benchmarks, our method outperforms strong baselines on 13 out of 19 tested tasks and matches the performance on the rest. Copyright 2024 by the author(s)
Background: The biggest challenge in our technologically advanced society is the healthy being of aging individuals and differently-abled people in our society. The leading cause for signifi-cant injuries and early de...
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