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Found 8 papers, 1 papers with code
LMM-Assisted Breast Cancer Treatment Target Segmentation with Consistency Embedding
Recent advancements in Artificial Intelligence (AI) have profoundly influenced medical fields, by providing tools to reduce clinical workloads.
LLM-driven Multimodal Target Volume Contouring in Radiation Oncology
Target volume contouring for radiation therapy is considered significantly more challenging than the normal organ segmentation tasks as it necessitates the utilization of both image and text-based clinical information.
K-SMPC: Koopman Operator-Based Stochastic Model Predictive Control for Enhanced Lateral Control of Autonomous Vehicles
Thus, we use the Koopman operator to represent the nonlinear dynamics of a vehicle in dynamic lane-keeping situations.
Uncertainty Quantification of Autoencoder-based Koopman Operator
We approximate the Koopman operator in a finite-dimensional space with the autoencoder, while the approximated Koopman has an approximation uncertainty.
RNN Controller for Lane-Keeping Systems with Robustness and Safety Verification
This paper proposes a Recurrent Neural Network (RNN) controller for lane-keeping systems, effectively handling model uncertainties and disturbances.
Classification Method of Road Surface Condition and Type with LiDAR Using Spatiotemporal Information
With the proposed DNN, we obtained the highest accuracy of 98. 0\% and 98. 6\% for two subregions near the vehicle.
Robust Control for Lane Keeping System Using Linear Parameter Varying Approach with Scheduling Variables Reduction
In this paper, to reduce the computational complexity, Principal Component Analysis (PCA)-based parameter reduction is performed to obtain a reduced model with a tighter convex set.
Intentional Deep Overfit Learning (IDOL): A Novel Deep Learning Strategy for Adaptive Radiation Therapy
Finally, in the sCT reconstruction task, the MAE is reduced from 68 to 22 HU by utilizing the IDOL framework.
