D. Nicholson

发表

DEEP NEURAL NETWORK MODELS OF OBJECT RECOGNITION EXHIBIT HUMAN-LIKE LIMITATIONS WHEN PERFORMING VISUAL SEARCH TASKS

A. Prinz, D. Nicholson, David A. Nicholson, 2021 .

Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study

A. Prinz, D. Nicholson, 2022, Journal of vision.

SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python

Joel Nothman, Robert T. McGibbon, K. Jarrod Millman, 2019, ArXiv.

Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python

Joel Nothman, Robert T. McGibbon, K. Jarrod Millman, 2020, Nature Methods.

Thalamostriatal and cerebellothalamic pathways in a songbird, the Bengalese finch

S. Sober, T. Roberts, D. Nicholson, 2017, bioRxiv.

Author Correction: SciPy 1.0: fundamental algorithms for scientific computing in Python

Johannes L. Schönberger, James T. Webber, Alessandro Pietro Bardelli, 2020, Nature Methods.

A Lightweight, Headphones-based System for Manipulating Auditory Feedback in Songbirds

Samuel J. Sober, David A. Nicholson, S. Sober, 2012, Journal of visualized experiments : JoVE.

Neural network models of object recognition can also account for visual search behavior

Astrid A. Prinz, David A. Nicholson, A. Prinz, 2020, bioRxiv.

SciPy 1.0: fundamental algorithms for scientific computing in Python

Johannes L. Schönberger, James T. Webber, Alessandro Pietro Bardelli, 2019, Nature Methods.

Convolutional neural networks performing a visual search task show attention-like limits on accuracy when trained to generalize across multiple search stimuli

Astrid A. Prinz, David A. Nicholson, A. Prinz, 2019, 2019 Conference on Cognitive Computational Neuroscience.

Comparison of machine learning methods applied to birdsong element classification

David A. Nicholson, D. Nicholson, 2016, SciPy.