A Modified Hierarchical Vision Transformer Model for Poultry Disease Detection
Published · IET Image Processing · Volume 19 · Issue 1 · e70115
Published in IET Image Processing, the study presents a modified hierarchical vision transformer for classifying poultry diseases from fecal images. The model combines multi-scale feature extraction with hierarchical attention to capture local and global visual patterns and achieved 90.90% average validation accuracy in the reported experiments.
Dacosta Agyei is listed as the second author.
Recorded contribution: Data curation · Methodology · Software · Writing — original draft