Andrew P. French

Plant Science · 2008–2017

A researcher in the Science corpus: 4 papers; trusts 11 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Plant Science — 42 citations into it; #5,513 of 8,232 by trust here, #4,150 by citations
• Computer Vision and Pattern Recognition — 40 citations into it
• Ecology — 19 citations into it; #7,309 of 10,717 by trust here, #6,072 by citations
• Analytical Chemistry — 15 citations into it; #961 of 1,254 by trust here, #771 by citations

Whom Andrew P. French trusts overall

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

1. Michael David Abràmoff
2. Massimo Minervini
3. D. Sims
4. Andrew P. Witkin
5. Dimitrios Moshou
6. John F. Canny
7. Hanno Scharr
8. Serge Beucher
9. Jan Behmann

Who trusts Andrew P. French overall

1. Samuel C. Hassler

Papers from Andrew P. French's perspective

Ordered by how strongly the researchers Andrew P. French trusts endorse each paper. Same corpus, a different order for every researcher.

1. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
2. A Computational Approach to Edge Detection
3. Random Walks for Image Segmentation
4. Annotated Image Datasets of Rosette Plants
5. Dynamics of seedling growth acclimation towards altered light conditions can be quantified via GROWSCREEN: a setup and procedure designed for rapid optical phenotyping of different plant species.
6. An Exemplar-Based CRF for Multi-instance Object Segmentation
7. A stereo imaging system for measuring structural parameters of plant canopies.
8. SPICY: towards automated phenotyping of large pepper plants in the greenhouse.
9. Rosette Tracker: An Open Source Image Analysis Tool for Automatic Quantification of Genotype Effects1[C][W]
10. 3-D Histogram-Based Segmentation and Leaf Detection for Rosette Plants

Their papers

• Leaf segmentation in plant phenotyping: a collation study (2015) — 281 citations
• Hyperspectral image analysis techniques for the detection and classification of the early onset of plant disease and stress (2017) — 566 citations
• Deep machine learning provides state-of-the-art performance in image-based plant phenotyping (2016) — 365 citations
• Colocalization of fluorescent markers in confocal microscope images of plant cells (2008) — 366 citations