2 papers
cs.CV2026
Relational Knowledge Distillation Brings DNN Representations Close Enough to Humans to Be Aligned Without Supervision
Yuria Shimizu, Soh Takahashi, Takato Horii +1
Linking the internal representations of deep neural networks (DNNs) to human mental representations is important for using DNNs as computational models of human vision. Existing DN…
cs.CV2025
Investigating Fine- and Coarse-grained Structural Correspondences Between Deep Neural Networks and Human Object Image Similarity Judgments Using Unsupervised Alignment
Soh Takahashi, Masaru Sasaki, Ken Takeda +1
The learning mechanisms by which humans acquire internal representations of objects are not fully understood. Deep neural networks (DNNs) have emerged as a useful tool for investig…