CS-Fnet: A Compressive Sampling Frequency Neural Network for Simultaneous Image Compression and Recognition

2021 ◽  
Author(s):  
Rui Ma ◽  
Qi Hao
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Sampling Frequency ◽  
Compressive Sampling

scholarly journals Target-Dependent Scalable Image Compression Using a Reconfigurable Recurrent Neural Network

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Sang Hoon Kim ◽  
Jae Hyun Park ◽  
Jong Hwan Ko
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Recurrent Neural Network

Image Compression Using Neural Network for Biomedical Applications

2018 ◽  
pp. 107-119
Author(s):  
G. Sasibhushana Rao ◽  
G. Vimala Kumari ◽  
B. Prabhakara Rao
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Biomedical Applications

Research On Image Compression Technology Based On Bp Neural Network

2018 ◽  
Author(s):  
CHENG-CHENG LI ◽  
GONG-FA LI ◽  
YING SUN ◽  
GUO-ZHANG JIANG ◽  
JIAN-YI KONG ◽  
...  
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Bp Neural Network

Medical Image Lossy Compression With LSTM Networks

2019 ◽  
pp. 47-68
Author(s):  
Nithin Prabhu G. ◽  
Trisiladevi C. Nagavi ◽  
Mahesha P.
Keyword(s):  
Neural Network ◽  
Image Compression ◽  
Recurrent Neural Network ◽  
Medical Image ◽  
Medical Images ◽  
Lossy Compression ◽  
Quality Aspect ◽  
Variable Compression

Medical images have a larger size when compared to normal images. There arises a problem in the storage as well as in the transmission of a large number of medical images. Hence, there exists a need for compressing these images to reduce the size as much as possible and also to maintain a better quality. The authors propose a method for lossy image compression of a set of medical images which is based on Recurrent Neural Network (RNN). So, the proposed method produces images of variable compression rates to maintain the quality aspect and to preserve some of the important contents present in these images.

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