2 citations · 5 across the 11 of their papers we have counts for
12 papers
Incorporating Visual Cortical Lateral Connection Properties into CNN: Recurrent Activation and Excitatory-Inhibitory Separation
Jin Hyun Park, Cheng Zhang, Yoonsuck Choe
The original Convolutional Neural Networks (CNNs) and their modern updates such as the ResNet are heavily inspired by the mammalian visual system. These models include afferent con…
Indexing Analytics to Instances: How Integrating a Dashboard can Support Design Education
Ajit Jain, Andruid Kerne, Nic Lupfer +9
We investigate how to use AI-based analytics to support design education. The analytics at hand measure multiscale design, that is, students' use of space and scale to visually and…
AdjointBackMapV2: Precise Reconstruction of Arbitrary CNN Unit's Activation via Adjoint Operators
Qing Wan, Siu Wun Cheung, Yoonsuck Choe
Adjoint operators have been found to be effective in the exploration of CNN's inner workings [1]. However, the previous no-bias assumption restricted its generalization. We overcom…
Meaning Versus Information, Prediction Versus Memory, and Question Versus Answer
Yoonsuck Choe
Brain science and artificial intelligence have made great progress toward the understanding and engineering of the human mind. The progress has accelerated significantly since the…
Emergence of Different Modes of Tool Use in a Reaching and Dragging Task
Khuong Nguyen, Yoonsuck Choe
Tool use is an important milestone in the evolution of intelligence. In this paper, we investigate different modes of tool use that emerge in a reaching and dragging task. In this…
AdjointBackMap: Reconstructing Effective Decision Hypersurfaces from CNN Layers Using Adjoint Operators
Qing Wan, Yoonsuck Choe
There are several effective methods in explaining the inner workings of convolutional neural networks (CNNs). However, in general, finding the inverse of the function performed by…