Learning to detect good 3D keypoints
The established approach to 3D keypoint detection consists in defining effective handcrafted
saliency functions based on geometric cues with the aim of maximizing keypoint …
saliency functions based on geometric cues with the aim of maximizing keypoint …
Concept activation vectors for generating user-defined 3D shapes
S Druc, A Balu, P Wooldridge… - Proceedings of the …, 2022 - openaccess.thecvf.com
We explore the interpretability of 3D geometric deep learning models in the context of
Computer-Aided Design (CAD). The field of parametric CAD can be limited by the difficulty of …
Computer-Aided Design (CAD). The field of parametric CAD can be limited by the difficulty of …
[PDF][PDF] 基于稀疏自动编码器算法的HBV 再激活分类预测模型
赵咏旺， 刘毅慧， 黄伟 - 智能计算机与应用, 2019 - cs.hit.edu.cn
原发性肝癌患者在接受精确放疗后易引起乙型肝炎病毒(HBV) 再激活. 本文的研究目的就是根据
已有的患者临床数据, 建立分类预测模型来及时做出预测防护, 从而在一定程度上降低HBV …
已有的患者临床数据, 建立分类预测模型来及时做出预测防护, 从而在一定程度上降低HBV …
[PDF][PDF] Evaluation of 3D Registration Deep Learning Methods Using Iterative Transformation Estimations
Abstract 3D registration is a process of aligning multiple three-dimensional (3D) data
structures (such as point clouds or meshes) and merging them into one consistent and …
structures (such as point clouds or meshes) and merging them into one consistent and …
Computer implemented method for generating a 3d object
R Ahlfeld, S Sathyanandha, P Wooldridge… - US Patent App. 18 …, 2024 - Google Patents
There is provided a method for a computer implemented method for generating a 3D object.
The method comprises training a machine learning system to learn design parameter values …
The method comprises training a machine learning system to learn design parameter values …