no code implementations • 12 May 2024 • jinhong Kim, Yongjun Ahn, Seungnyun Kim, Byonghyo Shim
Terahertz (THz) communications is considered as one of key solutions to support extremely high data demand in 6G.
1 code implementation • 7 May 2024 • Seungnyun Kim, Jihoon Moon, jinhong Kim, Yongjun Ahn, Donghoon Kim, Sunwoo Kim, Kyuhong Shim, Byonghyo Shim
Recently, we are witnessing the remarkable progress and widespread adoption of sensing technologies in autonomous driving, robotics, and metaverse.
no code implementations • 12 Mar 2024 • Yongjeong Oh, Jaehong Jo, Byonghyo Shim, Yo-Seb Jeon
The third framework is designed to accommodate the non-coherent scheme involving a small number of data bits, which simultaneously performs AD and DD.
no code implementations • 12 Dec 2023 • Jiyoung Kim, Kyuhong Shim, Insu Lee, Byonghyo Shim
In this paper, we propose a novel USS framework called Expand-and-Quantize Unsupervised Semantic Segmentation (EQUSS), which combines the benefits of high-dimensional spaces for better clustering and product quantization for effective information compression.
Ranked #3 on Unsupervised Semantic Segmentation on Potsdam-3
no code implementations • 25 Apr 2023 • Kyuhong Shim, Jiyoung Kim, Gusang Lee, Byonghyo Shim
Monocular depth estimation is very challenging because clues to the exact depth are incomplete in a single RGB image.
no code implementations • 10 Mar 2023 • Sunwoo Kim, Kyuhong Shim, Luong Trung Nguyen, Byonghyo Shim
Image text retrieval is a task to search for the proper textual descriptions of the visual world and vice versa.
no code implementations • 23 Feb 2023 • Xiaochun Ge, Shanping Yu, Wenqian Shen, Chengwen Xing, Byonghyo Shim
To acquire the dominating path gain information (DPGI, also regarded as the path gains of selected dominant paths) at the base station (BS), we propose a DPGI estimation and feedback scheme by jointly beamforming design at BS and RIS.
no code implementations • 2 Feb 2023 • Jiseob Kim, Kyuhong Shim, Junhan Kim, Byonghyo Shim
In AAM, the correlation between each patch feature and the synthetic image attribute is used as the importance weight for each patch.
no code implementations • 6 Sep 2022 • Yongjun Ahn, jinhong Kim, Seungnyun Kim, Kyuhong Shim, Jiyoung Kim, Sangtae Kim, Byonghyo Shim
Beamforming technique realized by the multiple-input-multiple-output (MIMO) antenna arrays has been widely used to compensate for the severe path loss in the millimeter wave (mmWave) bands.
no code implementations • 5 Sep 2022 • Wonjun Kim, Yongjun Ahn, jinhong Kim, Byonghyo Shim
Deep learning (DL), a branch of artificial intelligence (AI) techniques, has shown great promise in various disciplines such as image classification and segmentation, speech recognition, language translation, among others.
no code implementations • 29 Dec 2021 • Junhan Kim, Kyuhong Shim, Byonghyo Shim
Key idea of the proposed approach, henceforth referred to as semantic feature extraction-based GZSL (SE-GZSL), is to use the semantic feature containing only attribute-related information in learning the relationship between the image and the attribute.
1 code implementation • 2021 IEEE Workshop on Signal Processing Systems (SiPS) 2021 • Seokhyeon Choi, Kyuhong Shim, Jungwook Choi, Wonyong Sung, Byonghyo Shim
We propose TernGEMM, a special GEMM library using SIMD instructions for Deep Neural Network (DNN) inference with ternary weights and activations under 8-bit.
no code implementations • 11 Oct 2021 • Luong Trung Nguyen, Junhan Kim, Byonghyo Shim
Federated averaging (FedAvg) is a popular federated learning (FL) technique that updates the global model by averaging local models and then transmits the updated global model to devices for their local model update.
no code implementations • 19 Feb 2021 • Sun Hong Lim, Sunwoo Kim, Byonghyo Shim, Jun Won Choi
In this paper, we propose a deep learning-based beam tracking method for millimeter-wave (mmWave)communications.