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M. Crawford

4 papers hereh-index 417.8k citations222 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.HC1
  • eess.IV1
same name
  • M. Crawford — 4 papers, h 2
  • M. Crawford — 3 papers, h 11
  • M. Crawford — 3 papers, h 25
  • M. Crawford — 2 papers, h 41
  • M. Crawford — 2 papers, h 4
  • M. Crawford — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192021
most citedFeatureExplorer: Interactive Feature Selection and Exploration of Regression Models for Hyperspectral Images

28 citations · 29 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2021

Field-Based Plot Extraction Using UAV RGB Images

Changye Yang, Sriram Baireddy, Enyu Cai +2

Unmanned Aerial Vehicles (UAVs) have become popular for use in plant phenotyping of field based crops, such as maize and sorghum, due to their ability to acquire high resolution da…

eess.IV2021★ 1 cited

Panicle Counting in UAV Images For Estimating Flowering Time in Sorghum

Enyu Cai, Sriram Baireddy, Changye Yang +2

Flowering time (time to flower after planting) is important for estimating plant development and grain yield for many crops including sorghum. Flowering time of sorghum can be appr…

cs.CV2020

Deep Transfer Learning For Plant Center Localization

Enyu Cai, Sriram Baireddy, Changye Yang +2

Plant phenotyping focuses on the measurement of plant characteristics throughout the growing season, typically with the goal of evaluating genotypes for plant breeding. Estimating…

cs.HC2019★ 28 cited

FeatureExplorer: Interactive Feature Selection and Exploration of Regression Models for Hyperspectral Images

Jieqiong Zhao, Morteza Karimzadeh, Ali Masjedi +4

Feature selection is used in machine learning to improve predictions, decrease computation time, reduce noise, and tune models based on limited sample data. In this article, we pre…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.