zero-shot learning

In deep learning, images are utilized due to their rich information content, spatial hierarchies, and translation invariance, rendering them ideal for tasks such as object recognition and classification. The classification of malware using images is an important field for deep learning, especially in cybersecurity. Within this context, the Classified Advanced Persistent Threat Dataset is a thorough collection that has been carefully selected to further this field's study and innovation.

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MCAD contains 5 seen classed and 68939 cell samples, and the unseen class contains 6 categories and 32679 cell samples. Seen class samples are collected from fecal microscopic images, while unseen class samples are collected from leucorrhea microscopic images. 

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