Open AccessAn Accurate Detection System Based on the Convolutional Neural Network
Author(s) -
Xiangli Kong
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1650/3/032066
Subject(s) - convolutional neural network , computer science , residual neural network , artificial intelligence , deep learning , artificial neural network , pattern recognition (psychology) , machine learning
The purpose of this project is trying to detect tumors by computer based on deep learning techniques when a picture of a tumor is shown. In this research, a fast and accurate colon cancer detection is proposed, which means this research can dramatically increase the speed of diagnosis and can also improve the accuracy of confirming a diagnosis. During the experiment, a Convolutional Neural Network (CNN) structure akin to that of VGG Net and ResNet was built. A GPU computer with two 2080 Ti GPUs was used for training. The result of training produced 94% accuracy with a loss lower than 10%. Respectively, this result improved over 10% of accuracy compared to the detection by human eyes. Lastly, this program can be used by any computer to predict the tumor, which allows it transits to a practical tool in the future.