HIERARCHICAL IMAGE CLASSIFICATION USING TRANSFER LEARNING TO IMPROVE DEEP LEARNING MODEL PERFORMANCE FOR AMAZON PARROTS

Hierarchical image classification using transfer learning to improve deep learning model performance for amazon parrots

Abstract Numerous studies have proven the potential of deep learning models for classifying wildlife.Such models can reduce the workload of experts by automating species classification to monitor wild populations and global trade.Although deep learning models dual-penetration-strapon typically perform better with more input data, the available wild

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Memory T cells in latent Mycobacterium tuberculosis infection are directed against three antigenic islands and largely contained in a CXCR3+CCR6+ Th1 subset.

An understanding of the immunological footprint of Mycobacterium tuberculosis (MTB) CD4 T cell recognition is still incomplete.Here we report that human Th1 cells specific for MTB are largely contained in a CXCR3(+)CCR6(+) memory subset and highly focused on three broadly immunodominant antigenic islands, all related to bacterial secretion systems.

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