A Customized Approach to Compress the Images with Deep Learning Model for Embedded System


  • Abhiram Potlapalli, Seetharam Khetavath,


Customized CNN, Compressing Images, Embedded systems, deep learning, image processing.



The automated systems like embedded systems will work autonomously, take decisions and actions independently. And they will use small resources like compressed memory unit and processing. But if we want intelligent system then we should integrate Machine Learning (ML) then the agent will take decisions and actions its own be fully autonomous. But Theses embedded systems used in scientific community required high computational speed Despite this when we are working with images, the low capacity of embedded systems greatly hinders this integration, so the possibility of being able to integrate them into a wide range of micro-controllers can be a great advantage. So this paper implements a Customized intelligent system to take image and compress the size of it, and send it to embedded system to take intelligent decisions. The proposed system is competitive if compared to other commercial systems with optimal results.


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How to Cite

Abhiram Potlapalli,. (2024). A Customized Approach to Compress the Images with Deep Learning Model for Embedded System. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 2166–2172. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5813



Research Article