Marine Vertebrate Predator Detection and Recognition in Underwater Videos by Region Convolutional Neural Network

2019 ◽  
pp. 66-80 ◽  
Author(s):  
Mira Park ◽  
Wenli Yang ◽  
Zehong Cao ◽  
Byeong Kang ◽  
Damian Connor ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Predator Detection ◽  
Detection And Recognition

scholarly journals Improved Crack Detection and Recognition Based on Convolutional Neural Network

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Keqin Chen ◽  
Amit Yadav ◽  
Asif Khan ◽  
Yixin Meng ◽  
Kun Zhu
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Neural Networks ◽  
Convolutional Neural Network ◽  
Optimization Algorithm ◽  
Crack Detection ◽  
Recognition Rate ◽  
Machine Learning Methods ◽  
Long Time ◽  
Detection And Recognition

Concrete cracks are very serious and potentially dangerous. There are three obvious limitations existing in the present machine learning methods: low recognition rate, low accuracy, and long time. Improved crack detection based on convolutional neural networks can automatically detect whether an image contains cracks and mark the location of the cracks, which can greatly improve the monitoring efficiency. Experimental results show that the Adam optimization algorithm and batch normalization (BN) algorithm can make the model converge faster and achieve the maximum accuracy of 99.71%.

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