未成熟
发表于 2025-3-28 15:17:16
Machine Learning Approaches for Pap-Smear Diagnosis: An Overviewl data analysis problems, such as optimizing the Pap-Smear or Pap-Test diagnosis. Pap-Smear or Pap-Test is a method for diagnosing Cervical Cancer (4th leading cause of female cancer and 2nd common female cancer in the women aged 14–44 years old), invented by Dr. George Papanicolaou in 1928 (Bruni e
混沌
发表于 2025-3-28 19:00:08
Multi-kernel Analysis Paradigm Implementing the Learning from Loads Approach for Smart Power Systemsa new machine learning paradigm is presented focusing on the analysis of recorded electricity load data. The presented paradigm utilizes a set of multiple kernel functions to analyze a load signal into a set of components. Each component models a set of different data properties, while the coefficie
助记
发表于 2025-3-28 23:48:43
Conceptualizing and Measuring Energy Security: Geopolitical Dimensions, Data Availability, Quantitat to energy security research that aims to estimate a quantitative energy security index with a geopolitical focus, by providing an in-depth dynamic geopolitical look into the history, evolution, dimensions, data, estimation, taxonomy, and forecasts of energy security. Discussion is complemented with
GROG
发表于 2025-3-29 06:19:03
Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learning in which the process of forecasting is based on Machine Learning. The system has been developed following the cloud computing paradigm consisting of a backend application in Google’s API Hosting Cloud and using an Android front end using inspiring, contemporary styles of tools and libraries and har
Synovial-Fluid
发表于 2025-3-29 09:41:43
http://reply.papertrans.cn/63/6205/620411/620411_45.png
爵士乐
发表于 2025-3-29 12:12:05
http://reply.papertrans.cn/63/6205/620411/620411_46.png
Maximize
发表于 2025-3-29 16:38:39
http://reply.papertrans.cn/63/6205/620411/620411_47.png
博爱家
发表于 2025-3-29 21:16:11
Analytics and Evolving Landscape of Machine Learning for Emergency Responseision makers. This has resulted in new challenges related to the effective management of large volumes of data. In this regard, the role of machine learning in mass emergency and humanitarian crises is constantly evolving and gaining traction. As a branch of artificial intelligence, machine learning