Bria L Long

2018

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Bria L Long trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Kim F. Nimon
2. F. Oswald
3. Seyed-Mahdi Khaligh-Razavi

Papers from Bria L Long's perspective

Ordered by how strongly the researchers Bria L Long trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Supervised, but Not Unsupervised, Models May Explain IT Cortical Representation
2. Performance-optimized hierarchical models predict neural responses in higher visual cortex
3. Understanding the Results of Multiple Linear Regression
4. ImageNet classification with deep convolutional neural networks
5. ImageNet: A large-scale hierarchical image database
6. Distinctive Image Features from Scale-Invariant Keypoints
7. A Fast Learning Algorithm for Deep Belief Nets
8. Hierarchical models of object recognition in cortex
9. Gradient-based learning applied to document recognition
10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers

• The role of textural statistics vs. outer contours in deep CNN and neural responses to objects (2018) — 10 citations