Titlebook: Communication and Intelligent Systems; Proceedings of ICCIS Harish Sharma,Vivek Shrivastava,Lipo Wang Conference proceedings 2024 The Edito

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書目名稱Communication and Intelligent Systems影響因子(影響力)




書目名稱Communication and Intelligent Systems影響因子(影響力)學(xué)科排名




書目名稱Communication and Intelligent Systems網(wǎng)絡(luò)公開度




書目名稱Communication and Intelligent Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Communication and Intelligent Systems被引頻次




書目名稱Communication and Intelligent Systems被引頻次學(xué)科排名




書目名稱Communication and Intelligent Systems年度引用




書目名稱Communication and Intelligent Systems年度引用學(xué)科排名




書目名稱Communication and Intelligent Systems讀者反饋




書目名稱Communication and Intelligent Systems讀者反饋學(xué)科排名

拍下盜公款

Pattern of Lung Injury in CT/HRCT Using Deep Learning Techniques,ormance metrics with lower standard deviations over the test dataset. A possible future enhancement in this area could be the introduction of an ensemble architecture for classification which has the capability to process 3D images.

橢圓

COKE

Time Domain Specifications of Step Responses of Both Underdamped and Overdamped Systems: In Correctn a fixed value of 1(like . function), the algorithm addresses the flawed settling time calculations for both underdamped and overdamped systems. To check and compare the performance of the proposed algorithm, one overdamped system and two underdamped systems: one having some steady state error and

intolerance

高爾夫

A Study on DL for Pulmonary Embolism Prediction Harnessing Multimodal Data,ng DL-based multimodal early fusion features from Computed Tomography of Pulmonary Angiography (CTPA) images and six Electronic Medical Record (EMR) modalities are concatenated at the input level. The performance of the six DL models using the RadFusion dataset, a manually labeled and processed data

高爾夫

Performance Analysis of Machine Learning Algorithms Using Information Theoretic Class Based Multi-cheoretic dependent FSA. For our study, we considered twelve different machine learning algorithms for comparison using metrics such as accuracy, precision, recall and ROC-AUC curve. Results show a significant increase in accuracy of all the machine learning algorithms that are considered.

CARK

The Failure Recovery Management Framelet,ers and a performance assessment matrix are used to evaluate the quality of our model. All the features of the dataset and a subset of them were used to test the work that was suggested. Reducing the number of features influences the evaluation matrix and accuracy of algorithms. Utilizing a UCI set

爭(zhēng)吵加

Lecture Notes in Computer Scienceormance metrics with lower standard deviations over the test dataset. A possible future enhancement in this area could be the introduction of an ensemble architecture for classification which has the capability to process 3D images.

motivate

https://doi.org/10.1007/978-3-319-11245-9 (SVM), and Stochastic Gradient Descent (SGD) have been implemented on the thermal images for the classification of control and CVI subjects. The prediction performance of these ML models is assessed using evaluation measures such as accuracy, sensitivity, specificity, precision, F1 score, and AUC.