Titlebook: Advances and Applications of Artificial Intelligence & Machine Learning; Proceedings of ICAAA Bhuvan Unhelkar,Hari Mohan Pandey,Ankur Choud

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書目名稱Advances and Applications of Artificial Intelligence & Machine Learning影響因子(影響力)




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning影響因子(影響力)學(xué)科排名




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning網(wǎng)絡(luò)公開度




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning被引頻次




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning被引頻次學(xué)科排名




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning年度引用




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning年度引用學(xué)科排名




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning讀者反饋




書目名稱Advances and Applications of Artificial Intelligence & Machine Learning讀者反饋學(xué)科排名

碎石頭

https://doi.org/10.1007/978-3-031-13009-0ariants which are having current Avant-grade for object detection models, YOLOR and YOLOv5. Furthermore, we have inspected and evaluated the model performance by revising the predictions verified on the images of the test dataset.

cleaver

Paolo Verdecchia MD,Giuseppe Schillaci MDdered by means of IT boundaries. There are so many models for Workload Prediction in cloud data centers but most of them are static in nature. In this paper, we have proposed the LSTM model which is quite dynamic in nature and capable to remember previous time step information and this is how it learns.

Flatus

LIMIT

Subramanian Krishnan MD,William B. White MD) models, vgg16 and vgg19, are used along with the self-created dataset involving two classes: roads and crosswalks, which underwent the ML procedures resulting in the accurate detection of the respective classes.

Detain

Ambulatory Blood Pressure in Older Patients optimized number of virtual machines to be activated in the fog layer for active processing of the offloaded tasks. This schema decreases the delay-sensitive tasks queue waiting time and optimizes the required number of VMs in the fog layer. The efficacy of the proposed technique is validated with the help of simulation results.

遺棄

獨(dú)裁政府

Home (Self) Monitoring of Blood Pressurehm) to develop a smart helmet that is installed with additional voice assistant features to ease the experience for two-wheeler drivers. A prototype basic helmet design of helmet is provided that will be useful for further researchers and designers to develop more effective and better such systems in future.

暗語

龍蝦