FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification

FL-QNNs: Memory Efficient and Privacy Preserving Framework for Peripheral Blood Cell Classification

Human blood predominantly consists of plasma, erythrocytes, leukocytes, and thrombocytes. It is crucial for the transportation of oxygen and nutrients and for storing the health information of the human body. The body uses blood cells to fight against diseases and infections. Consequently, blood ana...

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Bibliographic Details
Main Authors: Meenakshi Aggarwal, Vikas Khullar, Nitin Goyal, Bhavani Sankar Panda, Hardik Doshi, Nafeesh Ahmad, Vivek Bhardwaj, Gaurav Sharma
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning
convolutional neural network
federated learning
quantized neural network
IID and non-IID
peripheral blood cell
Online Access:https://ieeexplore.ieee.org/document/11112772/
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https://ieeexplore.ieee.org/document/11112772/

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