Physics-Guided Neural Networks for Feedforward Control: An Orthogonal Projection-Based Approach

Assessment of Parkinson's Disease Severity from Videos Using Deep Architectures

Secure Logistic Regression for Vertical Federated Learning

Temporal Network Prediction and Interpretation

Reconstructing occluded Elevation Information in Terrain Maps with Self-supervised Learning

Learning for Control: An Inverse Optimization Approach

Development and testing of a prototype of a dental extraction trainer with real-time feedback on forces, torques, and angular velocity

Towards Unsupervised Rehabilitation: Development of a Portable Compliant Device for Sensorimotor Hand Rehabilitation

A Two-Stage Bayesian optimisation for Automatic Tuning of an Unscented Kalman Filter for Vehicle Sideslip Angle Estimation

Accurate Scene Text Detection via Scale-Aware Data Augmentation and Shape Similarity Constraint

Esophageal Tumor Segmentation in CT Images using a Dilated Dense Attention Unet (DDAUnet)

Selecting Informative Data Samples for Model Learning Through Symbolic Regression

Deep Recursive Embedding for High-Dimensional Data

Haptic training: Which types facilitate (re)learning of which motor task and for whom Answers by a review

R3L: Connecting Deep Reinforcement Learning To Recurrent Neural Networks For Image Denoising Via Residual Recovery

Visual Navigation in Real-World Indoor Environments Using End-to-End Deep Reinforcement Learning

Where to go next: Learning a Subgoal Recommendation Policy for Navigation in Dynamic Environments

Cross-View Matching for Vehicle Localization by Learning Geographically Local Representations

Electromagnetism in the Electrical Engineering Classroom: Dominant trends in teaching classical electromagnetic field theory and innovation vectors

Interactive Learning of Temporal Features for Control: Shaping Policies and State Representations From Human Feedback