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Full-Text Articles in Robotics

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman Aug 2020

A Review Paper: Analysis Of Weka Data Mining Techniques For Heart Disease Prediction System, Basma Jumaa Saleh, Ahmed Yousif Falih Saedi, Ali Talib Qasim Al-Aqbi, Lamees Abdalhasan Salman

Library Philosophy and Practice (e-journal)

Data mining is characterized as searching for useful information through very large data sets. Some of the key and most common techniques for data mining are association rules, classification, clustering, prediction, and sequential models. For a wide range of applications, data mining techniques are used. Data mining plays a significant role in disease detection in the health care industry. The patient should be needed to detect a number of tests for the disease. However, the number of tests should be reduced by using data mining techniques. In time and performance, this reduced test plays an important role. Heart disease is …


Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi Jan 2020

Comparison Of Object Detection And Patch-Based Classification Deep Learning Models On Mid- To Late-Season Weed Detection In Uav Imagery, Arun Narenthiran Veeranampalayam Sivakumar, Jiating Li, Stephen Scott, Eric T. Psota, Amit J. Jhala, Joe D. Luck, Yeyin Shi

Biological Systems Engineering: Papers and Publications

Mid- to late-season weeds that escape from the routine early-season weed management threaten agricultural production by creating a large number of seeds for several future growing seasons. Rapid and accurate detection of weed patches in field is the first step of site-specific weed management. In this study, object detection-based convolutional neural network models were trained and evaluated over low-altitude unmanned aerial vehicle (UAV) imagery for mid- to late-season weed detection in soybean fields. The performance of two object detection models, Faster RCNN and the Single Shot Detector (SSD), were evaluated and compared in terms of weed detection performance using mean …