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DeepCorn: A Semi-Supervised Deep Learning Method for High-Throughput Image-Based Corn Kernel Counting and Yield Estimation
In this paper, we propose a novel deep learning method for counting on-ear corn kernels in-field to aid in the gathering of real-time data and, ultimately, to improve decision making to maximize yield.
Convolutional Neural Networks for Image-based Corn Kernel Detection and Counting
The sliding window approach uses a convolutional neural network (CNN) for kernel detection.
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