COST AND BENEFIT OF NEAR-EARTH OBJECT DETECTION AND INTERCEPTION

2021 ◽  
pp. 1157-1190
Author(s):  
GREGORY H. CANAVAN
2012 ◽  
Author(s):  
Thomas G. Allen ◽  
Alan C. O'Connor ◽  
Igor Ternovskiy

Author(s):  
P. Rajan ◽  
P. Burlina ◽  
M. Chen ◽  
D. Edell ◽  
B. Jedynak ◽  
...  

Author(s):  
Jordan Riley ◽  
Philip Lubin ◽  
Gary B. Hughes ◽  
Hugh O'Neill ◽  
Peter Meinhold ◽  
...  

1993 ◽  
Author(s):  
George H. Noell ◽  
Frank M. Gresham
Keyword(s):  

2013 ◽  
Author(s):  
Sasitorn Srisawadi ◽  
◽  
Naraphorn Paoprasert ◽  
Prasit Wattanawongsakun ◽  
Sarawut Lerspalungsanti ◽  
...  

Author(s):  
Кonstantin А. Elshin ◽  
Еlena I. Molchanova ◽  
Мarina V. Usoltseva ◽  
Yelena V. Likhoshway

Using the TensorFlow Object Detection API, an approach to identifying and registering Baikal diatom species Synedra acus subsp. radians has been tested. As a result, a set of images was formed and training was conducted. It is shown that аfter 15000 training iterations, the total value of the loss function was obtained equal to 0,04. At the same time, the classification accuracy is equal to 95%, and the accuracy of construction of the bounding box is also equal to 95%.


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