Titlebook: Advanced Network Technologies and Intelligent Computing; Second International Isaac Woungang,Sanjay Kumar Dhurandher,Pradeepika Conference

SPIR

書目名稱Advanced Network Technologies and Intelligent Computing影響因子(影響力)




書目名稱Advanced Network Technologies and Intelligent Computing影響因子(影響力)學(xué)科排名




書目名稱Advanced Network Technologies and Intelligent Computing網(wǎng)絡(luò)公開(kāi)度




書目名稱Advanced Network Technologies and Intelligent Computing網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Advanced Network Technologies and Intelligent Computing被引頻次




書目名稱Advanced Network Technologies and Intelligent Computing被引頻次學(xué)科排名




書目名稱Advanced Network Technologies and Intelligent Computing年度引用




書目名稱Advanced Network Technologies and Intelligent Computing年度引用學(xué)科排名




書目名稱Advanced Network Technologies and Intelligent Computing讀者反饋




書目名稱Advanced Network Technologies and Intelligent Computing讀者反饋學(xué)科排名

Intervention

范例

Turnover in methyl groups in histonesy. Random Forest produced the most perfect result and Extreme Gradient Boost technique achieved an accuracy of 99.02%. Other Boosting classifiers, Gradient Boosting and Light Gradient Boosted Machine produced an accuracy of 94.16% and 98.38% respectively.

Callus

The pathogenesis of schizophreniacategories, which becomes an input to a U-Net architecture that encodes and decodes the layers and foretells the functioning of the heart through segmentation. In summary, the research covers designed architecture that presents state-of-the-art for investigating echocardiography information with its benefits and drawbacks continued by future work.

大溝

harrow

legitimate

Biochemistry of Sensory Functionseasure its performance. Other important parameters like prediction time and input resiliency are equally important. The paper deals with these issues in the context of SAR images. Experimental results show that deep learning models can be suitably applied in the domain of SAR image classification with the desired performance levels.

急性

好開(kāi)玩笑

安定