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Found 6 papers, 1 papers with code
Achieving Constraints in Neural Networks: A Stochastic Augmented Lagrangian Approach
Regularizing Deep Neural Networks (DNNs) is essential for improving generalizability and preventing overfitting.
Low-Resource White-Box Semantic Segmentation of Supporting Towers on 3D Point Clouds via Signature Shape Identification
In this paper, we propose SCENE-Net, a low-resource white-box model for 3D point cloud semantic segmentation.
Probabilistic Registration for Gaussian Process 3D shape modelling in the presence of extensive missing data
We propose a shape fitting/registration method based on a Gaussian Processes formulation, suitable for shapes with extensive regions of missing data.
GENEOnet: A new machine learning paradigm based on Group Equivariant Non-Expansive Operators. An application to protein pocket detection
Nowadays there is a big spotlight cast on the development of techniques of explainable machine learning.
Emotion pattern detection on facial videos using functional statistics
There is an increasing scientific interest in automatically analysing and understanding human behavior, with particular reference to the evolution of facial expressions and the recognition of the corresponding emotions.
From noisy point clouds to complete ear shapes: unsupervised pipeline
Ears are a particularly difficult region of the human face to model, not only due to the non-rigid deformations existing between shapes but also to the challenges in processing the retrieved data.
