Titlebook: Machine Learning and Data Mining in Pattern Recognition; 14th International C Petra Perner Conference proceedings 2018 Springer Internation

切口

書目名稱Machine Learning and Data Mining in Pattern Recognition影響因子(影響力)




書目名稱Machine Learning and Data Mining in Pattern Recognition影響因子(影響力)學(xué)科排名




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書目名稱Machine Learning and Data Mining in Pattern Recognition網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書目名稱Machine Learning and Data Mining in Pattern Recognition被引頻次




書目名稱Machine Learning and Data Mining in Pattern Recognition被引頻次學(xué)科排名




書目名稱Machine Learning and Data Mining in Pattern Recognition年度引用




書目名稱Machine Learning and Data Mining in Pattern Recognition年度引用學(xué)科排名




書目名稱Machine Learning and Data Mining in Pattern Recognition讀者反饋




書目名稱Machine Learning and Data Mining in Pattern Recognition讀者反饋學(xué)科排名

Abutment

Buttress

Fuzzy Networks Model, a Reliable Adoption in Corporations,s paper presents a Knowledge engineering application whereby a Fuzzy Network (FN) is used to build a complex computing model to reproduce corporate dynamics and to implement a Model Reference Adaptive Control (MARC) strategy for Corporate Control [.]. This model is used as a What If? Environment to

Peristalsis

過(guò)分

Understanding Customers and Their Grouping via WiFi Sensing for Business Revenue Forecasting,he most important components for the use of Internet access and other applications. In this work, we propose a WiFi-based sensing for store revenue forecasting by analyzing the customers’ behavior, especially the grouped customers’ behavior. Understanding customers’ behavior through WiFi-based sensi

refine

Scintigraphy

ARCHE

Predicting Social Unrest Using GDELT,wer of machine learning (Random Forests, Boosting, and Neural Networks) to try to explain and predict when huge social unrest events (Huge social unrest events are major social unrest events as recognized by Wikipedia page ‘List of incidents of civil unrest in the United States’) might unfold. We ex

Dislocation

Ten Years of Relevance Score for Content Based Image Retrieval,esults by filling the semantic gap between the user needs and the automatic image description provided by different image representations. Including the human in the loop through Relevance Feedback (RF) mechanisms turned out to help improving the retrieval results in CBIR. In this paper, we claim th

冒煙

When Different Is Wrong: Visual Unsupervised Validation for Web Information Extraction,action algorithm and hence further improve extraction results. The proposed validation method is unsupervised and can be integrated into most web information extraction systems effortlessly without any impact on existing processes, system’s robustness or maintenance. Instead of relying on visual pat