Search Results for author: Jihun Kim

Found 6 papers, 1 papers with code

Efficient Model Agnostic Approach for Implicit Neural Representation Based Arbitrary-Scale Image Super-Resolution

no code implementations20 Nov 2023 Young Jae Oh, Jihun Kim, Tae Hyun Kim

Single image super-resolution (SISR) has experienced significant advancements, primarily driven by deep convolutional networks.

Computational Efficiency Decoder +1

Deep Learning-based Synthetic High-Resolution In-Depth Imaging Using an Attachable Dual-element Endoscopic Ultrasound Probe

no code implementations13 Sep 2023 Hah Min Lew, Jae Seong Kim, Moon Hwan Lee, Jaegeun Park, Sangyeon Youn, Hee Man Kim, Jihun Kim, Jae Youn Hwang

The obtained results demonstrate that our proposed dual-element EUS probe with an image-to-image translation network has the potential to provide synthetic high-frequency ultrasound images deep inside tissues.

Image-to-Image Translation Super-Resolution

Learning Point Cloud Completion without Complete Point Clouds: A Pose-Aware Approach

no code implementations ICCV 2023 Jihun Kim, Hyeokjun Kweon, Yunseo Yang, Kuk-Jin Yoon

Our main idea is to generate multiple incomplete point clouds of various poses and integrate them into a complete point cloud.

Point Cloud Completion

High-level synthesis design of scalable ultrafast ultrasound beamformer with single FPGA

no code implementations6 Aug 2022 Zhengchang Kou, Qi You, Jihun Kim, Zhijie Dong, Matthew R. Lowerison, Nathiya V. Chandra Sekaran, Daniel A. Llano, Pengfei Song, Michael L. Oelze

Ultrafast ultrasound imaging is essential for advanced ultrasound imaging techniques such as ultrasound localization microscopy (ULM) and functional ultrasound (fUS).

6MapNet: Representing soccer players from tracking data by a triplet network

no code implementations10 Sep 2021 Hyunsung Kim, Jihun Kim, Dongwook Chung, Jonghyun Lee, Jinsung Yoon, Sang-Ki Ko

Although the values of individual soccer players have become astronomical, subjective judgments still play a big part in the player analysis.

Two-stage generative adversarial networks for document image binarization with color noise and background removal

1 code implementation20 Oct 2020 Sungho Suh, Jihun Kim, Paul Lukowicz, Yong Oh Lee

Document image enhancement and binarization methods are often used to improve the accuracy and efficiency of document image analysis tasks such as text recognition.

Binarization Decoder +1

Cannot find the paper you are looking for? You can Submit a new open access paper.