Efficient Autoencoder Architecture for Modeling the Lateral Geniculate Nucleus by Integrating Feedforward and Feedback Streams in the Human Visual System
The proposed pruned autoencoder (pAE) model effectively simulates the lateral geniculate nucleus (LGN) function by integrating feedforward and feedback streams from/to the primary visual cortex (V1), outperforming other models and human benchmarks in visual object categorization tasks.