Deep BiLSTM neural network model for emotion detection using cross-dataset approach

2022 ◽  
Vol 73 ◽  
pp. 103407
Author(s):  
Vaishali M. Joshi ◽  
Rajesh B. Ghongade ◽  
Aditi M. Joshi ◽  
Rushikesh V. Kulkarni
2021 ◽  
Author(s):  
Shi Feng ◽  
Jia Wei ◽  
Daling Wang ◽  
Xiaocui Yang ◽  
Zhenfei Yang ◽  
...  

Author(s):  
Seetharam .K ◽  
Sharana Basava Gowda ◽  
. Varadaraj

In Software engineering software metrics play wide and deeper scope. Many projects fail because of risks in software engineering development[1]t. Among various risk factors creeping is also one factor. The paper discusses approximate volume of creeping requirements that occur after the completion of the nominal requirements phase. This is using software size measured in function points at four different levels. The major risk factors are depending both directly and indirectly associated with software size of development. Hence It is possible to predict risk due to creeping cause using size.


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