Hyun Seok Yang

In this Letter, we propose a fast speckle noise reduction method with only a single reconstructed image based on convolutional neural networks. The proposed network has multi-sized kernels that can capture the speckle noise component effectively from digital holographic images. For robust noise reduction performance, the network is trained with a large noisy image dataset that has object-dependent noise and a wide range of noise levels. The experimental results show the fast, robust, and outstan

Slag foaming is a key factor in terms of quality and productivity in the electric arc furnace (EAF) steelmaking process. Optimal control of slag foaming is required, but is difficult due to the absence of practical on-line measuring methods and the broad process variability. In this study, a soft sensor model, which correlates the influential process variables with the slag foaming height, was developed by using machine learning based long short-term memory (LSTM) networks for modeling sequentia

This article proposes a design of a transformable mobile robot as a new concept of hybrid-type mobile robot in order to enhance mobility. Mobility considered in this work is based on stability, energy efficiency, and the capability to overcome obstacles. The proposed transformable mobile robot can change its bogie link lengths and wheel size. The relationships between mobility and the link length and the wheel size are studied. Its stability, energy efficiency, and the capability to overcome obs

Digital holography is the best tool for measuring object information data. Parallel phase-shift digital holography (PPSDH) is particularly suitable for measuring moving objects. This method generates images of objects, but the image quality is diminished because they contain abundant speckle noise. In this paper, we propose an interpolation-based algorithm to reduce the levels of speckle noise in images generated by PPSDH, thus enhancing their quality.

Abstract Digital holographic imaging systems are promising three-dimensional imaging systems that acquire holograms via interference of a reference wave and an object wave. Using digital holography and the numerical diffraction theory, an image can be reconstructed at any distance from the hologram. However, accurate determination of the distance of the object from the hologram is required to focus the image. Various autofocusing algorithms have been studied. The conventional autofocusing algori

Slip detection is an essential technology for robotic grippers to autonomously grasp unknown objects and can be achieved using a tactile sensor.In this paper, we propose a high-performance multilayer-perceptron-based slip detection algorithm that utilizes only normal force data obtained by frequency selective surface(FSS) sensor arrays.This is achieved in three stages in this study.First, slip and no-slip training data are aggregated such that the data closely resemble those of the real world.Se