A dangerous hematological malignancy, acute lymphoblastic leukemia (ALL) has a survival rate that is drastically affected by how long it takes to diagnose the disease. Though convolutional neural ...
This work presents a comprehensive analysis of how extreme data quantization and fixed pattern noise (FPN) from CMOS imagers affect the performance of deep neural networks for image recognition tasks.
The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.
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