Concept

Recherche automatique d'architecture neuronale

Publications associées (159)

What Makes for Automatic Reconstruction of Pulmonary Segments

Jiancheng Yang, Li Zhang, Hongwei Li, Bo Du, Jingyu Li

3D reconstruction of pulmonary segments plays an important role in surgical treatment planning of lung cancer, which facilitates preservation of pulmonary function and helps ensure low recurrence rates. However, automatic reconstruction of pulmonary segmen ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Landmark Regularization: Ranking Guided Super-Net Training in Neural Architecture Search

Mathieu Salzmann, Kaicheng Yu

Weight sharing has become a de facto standard in neural architecture search because it enables the search to be done on commodity hardware. However, recent works have empirically shown a ranking disorder between the performance of stand-alone architectures ...

IEEE COMPUTER SOC2021

From Human-Designed Convolutional Neural Networks Towards Robust Neural Architecture Search

Kaicheng Yu

Artificial intelligence has been an ultimate design goal since the inception of computers decades ago. Among the many attempts towards general artificial intelligence, modern machine learning successfully tackles many complex problems thanks to the progres ...

EPFL2021

Dataset of "Resonant Band-Edge Emissive States in Strongly Confined CsPbBr3 Perovskite Nanoplatelets"

Jacques-Edouard Moser, Etienne Christophe Socie, Brener Rodrigo De Carvalho Vale, Aaron Tomas Terpstra

Dataset underpinning the published article: Resonant Band-Edge Emissive States in Strongly Confined CsPbBr3 Perovskite Nanoplatelets. J. Phys. Chem. C, 2021, . DOI: 10.1021/acs.jpcc.1c01353 ...

2021

Multiscale Representation Learning of Graph Data With Node Affinity

Pascal Frossard, Chenglin Li, Xing Gao

Graph neural networks have emerged as a popular and powerful tool for learning hierarchical representation of graph data. In complement to graph convolution operators, graph pooling is crucial for extracting hierarchical representation of data in graph neu ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Prediction of the reaction forces of spiral-groove gas journal bearings by artificial neural network regression models

Jürg Alexander Schiffmann, Elia Iseli

This paper presents neural network regression models for predicting the nonlinear static and linearized dynamic reaction forces of spiral grooved gas journal bearings. The partial differential equations (PDEs) are sampled, based on a full factorial and ran ...

2021

Active Subdivision Surfaces for the Semiautomatic Segmentation of Biomedical Volumes

Michaël Unser, Anaïs Laure Marie-Thérèse Badoual

We present a new family of active surfaces for the semiautomatic segmentation of volumetric objects in 3D biomedical images. We represent our deformable model by a subdivision surface encoded by a small set of control points and generated through a geometr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Generating Smooth Pose Sequences for Diverse Human Motion Prediction

Mathieu Salzmann, Wei Mao

Recent progress in stochastic motion prediction, i.e., predicting multiple possible future human motions given a single past pose sequence, has led to producing truly diverse future motions and even providing control over the motion of some body parts. How ...

IEEE2021

Learning Saliency From Single Noisy Labelling: A Robust Model Fitting Perspective

Tong Zhang

The advances made in predicting visual saliency using deep neural networks come at the expense of collecting large-scale annotated data. However, pixel-wise annotation is labor-intensive and overwhelming. In this paper, we propose to learn saliency predict ...

2021

Human-Centered Scene Understanding via Crowd Counting

Weizhe Liu

Human-centered scene understanding is the process of perceiving and analysing a dynamic scene observed through a network of sensors with emphasis on human-related activities. It includes the visual perception of human-related activities from either single ...

EPFL2021

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