Kerry Brian Walsh

Computer Vision and Pattern Recognition · 2005–2021

A researcher in the Science corpus: 12 papers; trusts 134 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 40 citations into it
• Analytical Chemistry — 38 citations into it; #452 of 1,254 by trust here, #248 by citations
• Plant Science — 32 citations into it; #3,867 of 8,232 by trust here, #3,913 by citations
• Artificial Intelligence — 18 citations into it
• Biophysics — 6 citations into it
• Environmental Engineering — 6 citations into it
• Model Architectures — 5 citations into it

Whom Kerry Brian Walsh trusts overall

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

1. Ross B. Girshick
2. Kaiming He
3. Karen Simonyan
4. Suchet Bargoti
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Matthew D. Zeiler
8. Andrew Zisserman
9. Yann LeCun
10. Jia Deng

Who trusts Kerry Brian Walsh overall

1. Puneet Mishra
2. Suchet Bargoti
3. James Patrick Underwood
4. Anand Koirala
5. Dhivya Elavarasan
6. Ramin Nikzad‐Langerodi

Papers from Kerry Brian Walsh's perspective

Ordered by how strongly the researchers Kerry Brian Walsh trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

Their papers

• Achieving robustness across season, location and cultivar for a NIRS model for intact mango fruit dry matter content. II. Local PLS and nonlinear models (2021) — 62 citations
• Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use (2020) — 354 citations
• Assessment of avocado fruit dry matter content using portable near infrared spectroscopy: Method and instrumentation optimisation (2020) — 60 citations
• Achieving robustness across season, location and cultivar for a NIRS model for intact mango fruit dry matter content (2020) — 105 citations
• Achieving robustness to temperature change of a NIRS-PLSR model for intact mango fruit dry matter content (2020) — 52 citations
• NIRS prediction of dry matter content of single olive fruit with consideration of variable sorting for normalisation pre-treatment (2020) — 55 citations
• Deep learning - Method overview and review of use for fruit detection and yield estimation (2019) — 518 citations
• Deep learning for real-time fruit detection and orchard fruit load estimation: benchmarking of ‘MangoYOLO’ (2019) — 417 citations
• Assessment of internal flesh browning in intact apple using visible-short wave near infrared spectroscopy (2016) — 58 citations
• Estimating mango crop yield using image analysis using fruit at 'stone hardening' stage and night time imaging (2014) — 124 citations
• Non-invasive techniques for measurement of fresh fruit firmness. (2009) — 73 citations
• Assessment of internal quality attributes of mandarin fruit. 1. NIR calibration model development (2005) — 95 citations