[PDF] Invariant visual representation by single neurons in the human brain | Semantic Scholar

This thesis discusses the issue of how best to quantify sparseness, particularly in very sparse systems where biases are significant, and shows results obtained by applying an existing model of sparse coding both to unsupervised category discovery in images and to differentiation between images of different individuals.

Evidence from the fields of psychology, neuropsychology, and neurophysiology supports the idea that there are multiple systems for recognition of objects, and indicates that one system may represent objects by combinations of multiple views, or aspects, and another may represent Objects by structural primitives and their spatial interrelationships.