Titlebook: Computer, Communication, and Signal Processing; 6th IFIP TC 5 Intern Erich J. Neuhold,Xavier Fernando,Aravindan Chandra Conference proceedi

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书目名称Computer, Communication, and Signal Processing影响因子(影响力)




书目名称Computer, Communication, and Signal Processing影响因子(影响力)学科排名




书目名称Computer, Communication, and Signal Processing网络公开度




书目名称Computer, Communication, and Signal Processing网络公开度学科排名




书目名称Computer, Communication, and Signal Processing被引频次




书目名称Computer, Communication, and Signal Processing被引频次学科排名




书目名称Computer, Communication, and Signal Processing年度引用




书目名称Computer, Communication, and Signal Processing年度引用学科排名




书目名称Computer, Communication, and Signal Processing读者反馈




书目名称Computer, Communication, and Signal Processing读者反馈学科排名

不理会

Predicting Students’ Satisfaction Towards Online Courses Using Aspect-Based Sentiment Analysisrence to the online courses using machine learning algorithm. The proposed system has attained improved accuracy than the existing model. From this study, the specific aspects are obtained using both unsupervised and semi-supervised LDA algorithms. Students’ satisfaction with specific aspects of the

Jargon

Detection and Classification of Paddy Leaf Diseases Using Deep Learning (CNN)af blight, rice blast, brown spot, rymv and rice tungro for processing the image. In pre-processing, background exclusion is done based on the hue value to extract the non-diseased and diseased part. Feature Extraction is executed by applying Convolutional Neural Network. The proposed system achieve

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REIGN

REIGN

Automated Annotation and Classification of Catheters in Chest X-Raystional number of classes, custom loss function, and attention heads introduced in the model is a unique attempt to ensure robust results in the radiological inferences. It is evident that the qualitative and quantitative results of annotation and classification are viable which resembles how humans

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宇宙你

Trust Aware Secure Routing Model in MANET: Self-improved Particle Swarm Optimization for Optimal Rou considering certain parameters like trust rate (security), Packet Drop Ratio (PDR) distance, congestion, energy, and as well. The performance of the adopted work is examined to the existing schemes regarding Energy, Delay, and Network Lifetime.

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