| contributor author | Serkan Tapkın | |
| contributor author | Burak Şengöz | |
| contributor author | Gökhan Şengül | |
| contributor author | Ali Topal | |
| contributor author | Erol Özçelik | |
| date accessioned | 2017-05-08T21:41:08Z | |
| date available | 2017-05-08T21:41:08Z | |
| date copyright | September 2015 | |
| date issued | 2015 | |
| identifier other | %28asce%29cp%2E1943-5487%2E0000363.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/59333 | |
| description abstract | The goal of this study is to design an expert system that automatically classifies the microscopic images of polypropylene fiber (PPF) modified bitumen including seven different contents of fibers. Optical microscopy was used to capture the images from thin films of polypropylene fiber modified bitumen samples at a magnification scale of 100 ×. A total of 313 images were pre-processed, and features were extracted and selected by the exhaustive search method. The | |
| publisher | American Society of Civil Engineers | |
| title | Estimation of Polypropylene Concentration of Modified Bitumen Images by Using k-NN and SVM Classifiers | |
| type | Journal Paper | |
| journal volume | 29 | |
| journal issue | 5 | |
| journal title | Journal of Computing in Civil Engineering | |
| identifier doi | 10.1061/(ASCE)CP.1943-5487.0000353 | |
| tree | Journal of Computing in Civil Engineering:;2015:;Volume ( 029 ):;issue: 005 | |
| contenttype | Fulltext | |
