Zobrazeno 1 - 10
of 39 528
pro vyhledávání: '"Lee, Jung In"'
Person detection and tracking (PDT) has seen significant advancements with 2D camera-based systems in the autonomous vehicle field, leading to widespread adoption of these algorithms. However, growing privacy concerns have recently emerged as a major
Externí odkaz:
http://arxiv.org/abs/2408.05940
Autor:
Xu, Zhongweiyang, Aroudi, Ali, Tan, Ke, Pandey, Ashutosh, Lee, Jung-Suk, Xu, Buye, Nesta, Francesco
This paper presents a novel multi-channel speech enhancement approach, FoVNet, that enables highly efficient speech enhancement within a configurable field of view (FoV) of a smart-glasses user without needing specific target-talker(s) directions. It
Externí odkaz:
http://arxiv.org/abs/2408.06468
Autor:
Yousif, Mustafa Z., Zhou, Dan, Yu, Linqi, Zhang, Meng, Mohammadikarachi, Arash, Lee, Jung Sub, Lim, Hee-Chang
This study aims to reconstruct the complete flow field from spatially restricted domain data by utilizing an Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) model. The difficulty in flow field reconstruction lies in accurately captu
Externí odkaz:
http://arxiv.org/abs/2408.01658
Autor:
Lee, Jung Hyun, Kim, Jeonghoon, Yang, June Yong, Kwon, Se Jung, Yang, Eunho, Yoo, Kang Min, Lee, Dongsoo
With the commercialization of large language models (LLMs), weight-activation quantization has emerged to compress and accelerate LLMs, achieving high throughput while reducing inference costs. However, existing post-training quantization (PTQ) techn
Externí odkaz:
http://arxiv.org/abs/2407.11534
Large Language Models (LLMs) have demonstrated impressive problem-solving capabilities in mathematics through step-by-step reasoning chains. However, they are susceptible to reasoning errors that impact the quality of subsequent reasoning chains and
Externí odkaz:
http://arxiv.org/abs/2407.12863
Autor:
Park, Chanyong, Lee, Jung Hun
Applying the holographic method, we investigate an RG flow and IR physics holographically when a two-dimensional conformal field theory is deformed by a relevant scalar operator. To do so, we first assume an RG flow from a UV to new IR CFT. On the du
Externí odkaz:
http://arxiv.org/abs/2406.17221
Autor:
Hou, Benjamin, Lee, Sung-Won, Lee, Jung-Min, Koh, Christopher, Xiao, Jing, Pickhardt, Perry J., Summers, Ronald M.
Purpose: To evaluate the performance of an automated deep learning method in detecting ascites and subsequently quantifying its volume in patients with liver cirrhosis and ovarian cancer. Materials and Methods: This retrospective study included contr
Externí odkaz:
http://arxiv.org/abs/2406.15979
The genus-$g$ Goeritz group is the group of isotopy classes of orientation-preserving self-homeomorphisms of the $3$-sphere that preserve the genus-$g$ Heegaard splitting of the $3$-sphere. In 1933, Goeritz found first a finite generating set of the
Externí odkaz:
http://arxiv.org/abs/2406.13309
Autor:
Lee, Jung H., Vijayan, Sujith
Deep learning (DL) enables deep neural networks (DNNs) to automatically learn complex tasks or rules from given examples without instructions or guiding principles. As we do not engineer DNNs' functions, it is extremely difficult to diagnose their de
Externí odkaz:
http://arxiv.org/abs/2405.20605
In this paper, we introduce a novel approach to user-centric association and feedback bit allocation for the downlink of a cell-free massive MIMO (CF-mMIMO) system, operating under limited feedback constraints. In CF-mMIMO systems employing frequency
Externí odkaz:
http://arxiv.org/abs/2405.11563