Samsung Sds Co., Ltd.

Korea Institute of Science and Technology

JoonSeok Lee

JoonHo Lee

SooAh Cho

Minyoung Lee

Jieun Song

Eunyoung Jeon

Provided are a method of manufacturing a stent for drug release that may be coated with a drug by forming a 3D nanostructured film on the surface of a stent and a stent for drug release manufactured thereby, more particularly, a method of manufacturing a stent for drug release including: (a) preparing a stent, (b) forming a 3D nanostructured film on a surface of the stent; and (c) surface-treating the 3D nanostructured film, and a stent for drug release manufactured thereby.

Method for manufacturing stent for drug release, including flexible nanostructured film connected in three dimensions, and stent for drug release prepared thereby

An apparatus is for unsupervised domain adaptation for allowing a deep learning model with supervised learning on a source domain completed to be subjected to unsupervised domain adaptation to a target domain. The apparatus includes a first learning unit to perform a forward pass by inputting a pair (x, y) of first data xof the source domain and a label yfor each of the first data and second data xbelonging to the target domain, and insert a dropout following a Bernoulli distribution into the deep learning model in performing the forward pass, and a second learning unit to perform a back propagation to minimize uncertainty about the learning parameter of the deep learning model by using a predicted value for each class output through the forward pass and the label y, and an uncertainty vector for the second data xoutput through the forward pass as inputs.

Apparatus and method for unsupervised domain adaptation

A few-shot learning method according to an embodiment may be performed in a computing device including one or more processors and a memory storing one or more programs executed by the one or more processors. The method may include performing a first task for subjecting a first model to few-shot learning (FSL) based on one or more meta-training data and performing a second task for subjecting a second model to supervised learning based on one or more derived data modified from the one or more meta-training data.

Growing community of inventors

Seoul, South Korea

JoonSeok Lee