In this paper, we derived closed-form expressions for the EM updates in the 2MLR problem. Notably, in the noiseless setting we first showed and then analyzed the cycloid trajectory of EM updates. Additionally, we demonstrated the quadratic convergence rate for regression parameters, which is independent of mixing weights. We emphasized that errors in mixing weights primarily arise from the angle formed between true and estimated regression parameters. Finally, we conducted a detailed analysis of the statistical errors in the estimation of regression parameters and mixing weights.
In this paper, we presented the use of GAN generated synthetic images to augment the training data for panicle detection and counting. We examined two image-to-image translation GANs and showed that their use can improve the performance of panicle detection and counting. We did not use the temporal information available in our real Sorghum UAV dataset during training due to the limitation of the network structures. Future work includes developing multi-temporal methods that can generate synthetic plant images in a temporally consistent style. This will also us to estimate phenotypic traits as the plant grows. We will also examine our approach for estimating traits of other plant such as maize tassels.
The paper describes the work of the authors in making the Smart Ladle, an ongoing project to develop a machine-learning tool that uses industry process data to predict future behavior in the steel refining and casting processes. Using information gathered by SDI Butler Division, the Smart Ladle builds connections between the different inputs (such as a ladle’s history) and the temperature of the steel in the continuous caster.
The paper proposes a structured light vision system equipped with multi-cameras and multi-laser emitters for object height measurement or 3D reconstruction. The proposed method offers a better accuracy performance over a single camera system. To …
Compared the proposed MLRANSAC method with time-division and color division methods, the experiment results validated the effectiveness of the MLRANSAC algorithm.