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2022

Adke, Shrinidhi; Li, Changying; Rasheed, Khaled M.; Maier, Frederick W.

Supervised and Weakly Supervised Deep Learning for Segmentation and Counting of Cotton Bolls Using Proximal Imagery Journal Article

In: Sensors, vol. 22, no. 10, 2022, ISSN: 1424-8220.

Abstract | Links | BibTeX | Tags: deep learning, machine learning

Tan, Chenjiao; Li, Changying; He, Dongjian; Song, Huaibo

Towards real-time tracking and counting of seedlings with a one-stage detector and optical flow Journal Article

In: Computers and Electronics in Agriculture, vol. 193, pp. 106683, 2022, ISSN: 0168-1699.

Abstract | Links | BibTeX | Tags: Cotton seedling, Counting, Deep convolutional neural network, deep learning, machine learning, object detection, Optical flow

Petti, Daniel; Li, Changying

Weakly-supervised learning to automatically count cotton flowers from aerial imagery Journal Article

In: Computers and Electronics in Agriculture, vol. 194, pp. 106734, 2022, ISSN: 0168-1699.

Abstract | Links | BibTeX | Tags: Active learning, deep learning, High-throughput phenotyping, machine learning, Multiple-instance learning, Object counting

2021

Ni, Xueping; Li, Changying; Jiang, Huanyu; Takeda, Fumiomi

Three-dimensional photogrammetry with deep learning instance segmentation to extract berry fruit harvestability traits Journal Article

In: ISPRS Journal of Photogrammetry and Remote Sensing, vol. 171, pp. 297-309, 2021, ISSN: 0924-2716.

Abstract | Links | BibTeX | Tags: 2D-3D projection, 3D reconstruction, Blueberry traits, deep learning, machine learning, mask R-CNN

2020

Adke, S.; Mogel, K. H. Von; Jiang, Y.; Li, C.

Instance Segmentation to Estimate Consumption of Corn Ears by Wild Animals for GMO Preference Tests Journal Article

In: Frontiers in Artificial Intelligence, vol. 3, no. 119, 2020.

Links | BibTeX | Tags: deep learning, machine learning, mask R-CNN

Jiang, Y.; Li, C.; Xu, R.; Sun, S.; Robertson, J. S.; Paterson, A. H.

DeepFlower: a deep learning-based approach to characterize flowering patterns of cotton plants in the field Journal Article

In: Plant Methods, vol. 16, no. 156, 2020.

Links | BibTeX | Tags: deep learning, machine learning

Ni, X.; Li, C.; Jiang, H.; Takeda., F.

Deep learning image segmentation and extraction of blueberry fruit traits associated with harvestability and yield Journal Article

In: Horticulture Research, vol. 7, no. 1, pp. 1-14, 2020.

Links | BibTeX | Tags: deep learning, machine learning

Jiang, Yu; Li, Changying

Convolutional neural networks for image-based high throughput plant phenotyping: A review Journal Article

In: Plant Phenomics, vol. 2020, no. 4152816, 2020.

Links | BibTeX | Tags: CNN, deep learning, machine learning, review

Zhang, M.; Jiang, Y.; Li, C.; Yang, F.

Fully convolutional networks for blueberry bruising and calyx segmentation using hyperspectral transmittance imaging Journal Article

In: Biosystems Engineering, vol. 192, pp. 159-175, 2020.

Links | BibTeX | Tags: deep learning, hyperspectral, machine learning

2019

Jiang, Y.; Li, C.; Paterson, A.; Robertson, J.

DeepSeedling: Deep convolutional network and Kalman filter for plant seedling detection and counting in the field Journal Article

In: Plant Methods, vol. 15, no. 1, pp. 141, 2019.

Links | BibTeX | Tags: deep learning, machine learning

2017

Xu, R.; Li, C.; Paterson, A. H.; Jiang, Y.; Sun, S.; Roberson, J.

Aerial Images and Convolutional Neural Network for Cotton Bloom Detection Journal Article

In: Frontiers in Plant Sciences, 8, 2235, 2017.

Abstract | Links | BibTeX | Tags: deep learning, High-throughput phenotyping, machine learning