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Found 5 papers, 1 papers with code
Modified CycleGAN for the synthesization of samples for wheat head segmentation
Using this approach, we developed a realistic annotated synthetic dataset for wheat head segmentation.
RIDGE: Reproducibility, Integrity, Dependability, Generalizability, and Efficiency Assessment of Medical Image Segmentation Models
Deep learning techniques, despite their potential, often suffer from a lack of reproducibility and generalizability, impeding their clinical adoption.
Generalizability of Machine Learning Models: Quantitative Evaluation of Three Methodological Pitfalls
We investigate three methodological pitfalls: (1) violation of independence assumption, (2) model evaluation with an inappropriate performance indicator or baseline for comparison, and (3) batch effect.
Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? -- A Case Study using Dual Energy CT Data
In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i. e. binary code which can be executed but is difficult to be understood by a potential attacker.
Crop Lodging Prediction from UAV-Acquired Images of Wheat and Canola using a DCNN Augmented with Handcrafted Texture Features
In this paper, we propose a deep convolutional neural network (DCNN) architecture for lodging classification using five spectral channel orthomosaic images from canola and wheat breeding trials.
