Titlebook: Next Generation Computing Technologies on Computational Intelligence; 4th International Co Manish Prateek,Durgansh Sharma,Neeraj Kumar Conf

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書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence影響因子(影響力)學(xué)科排名




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書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence被引頻次




書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence被引頻次學(xué)科排名




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書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence年度引用學(xué)科排名




書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence讀者反饋




書(shū)目名稱Next Generation Computing Technologies on Computational Intelligence讀者反饋學(xué)科排名

Creatinine-Test

Emotion Recognition in Poetry Using Ensemble of Classifiersposed emotion recognition model uses a novel ensemble classifier schema based on SVM, Logistic regression, NB Classifier, and Emotion Modifier Preserved Vector Space Model. The results show that the proposed model achieves satisfactory precision, Recall and F-measure in recognizing emotions from poems.

V切開(kāi)

An Approach to Threshold Based Human Skin Color Recognition and Segmentation in Different Color Mode differentiate the color and luminance information still in the uncharacteristic illumination circumstances. The investigational outcome illustrates the effectiveness of color model based recognition of skin tone in color images.

凹槽

Harridan

Distributed Multi-criteria Based Clusterhead Selection Approach for MANETn NS-2.35. Experimental results show that the proposed DMBCA achieves much better results in terms of performance parameters such as packet delivery ratio, average throughput and routing overhead than conventional AODV technique.

傀儡

NStackSenti: Evaluation of a Multi-level Approach for Detecting the Sentiment of Usersenti is applied on two separate datasets to demonstrate the effectiveness in terms of accuracy. NStackSenti provides better accuracy with trigram than unigram and bigram. It provides 83.7% and 86.24% accuracy on 2000 and 50000 data respectively.

南極

legislate

Increment

蜈蚣

Parkinson’s Disease Diagnosis by fMRI Images Using MFCC Feature Extraction feature extraction of fMRI images. Mean and Standard deviation of the extracted coefficients was calculated which was further classified using the Classifier Learner. Obtained results showed that MFCC coefficients are effectively able to identify PD and normal person.