Resource Optimized Neural Architecture Search for 3D Medical Image Segmentation

no code implementations • 2 Sep 2019 • Woong Bae, Seungho Lee, Yeha Lee, Beomhee Park, Minki Chung, Kyu-Hwan Jung

We propose the resource-optimized neural architecture search method which can be applied to 3D medical segmentation tasks in a short training time (1. 39 days for 1GB dataset) using a small amount of computation power (one RTX 2080Ti, 10. 8GB GPU memory).

Image Segmentation Medical Image Segmentation +3

CRAM: Clued Recurrent Attention Model

no code implementations • 28 Apr 2018 • Minki Chung, Sungzoon Cho

To overcome the poor scalability of convolutional neural network, recurrent attention model(RAM) selectively choose what and where to look on the image.

Image Classification

Squeezed Convolutional Variational AutoEncoder for Unsupervised Anomaly Detection in Edge Device Industrial Internet of Things

no code implementations • 18 Dec 2017 • Dohyung Kim, Hyochang Yang, Minki Chung, Sungzoon Cho

In this paper, we propose Squeezed Convolutional Variational AutoEncoder (SCVAE) for anomaly detection in time series data for Edge Computing in Industrial Internet of Things (IIoT).

Edge-computing Time Series +2