Zobrazeno 1 - 10
of 865
pro vyhledávání: '"Sebin A"'
This study proposes a modularized deep learning-based loading protocol for optimal parameter estimation of Bouc-Wen (BW) class models. The protocol consists of two key components: optimal loading history construction and CNN-based rapid parameter est
Externí odkaz:
http://arxiv.org/abs/2411.02776
State-of-the-art text-to-image (T2I) diffusion models often struggle to generate rare compositions of concepts, e.g., objects with unusual attributes. In this paper, we show that the compositional generation power of diffusion models on such rare con
Externí odkaz:
http://arxiv.org/abs/2410.22376
Autor:
John, Sebin, West, Michael E.
The methodology developed by McNamara and Bulland (2004) for computing Power Spectral Densities (PSDs) has gained popularity due to its low computational cost and reduction of spectral variance. This methodology is widely used in seismic noise studie
Externí odkaz:
http://arxiv.org/abs/2410.14071
Autor:
Im, Woobin, Cha, Geonho, Lee, Sebin, Lee, Jumin, Seon, Juhyeong, Wee, Dongyoon, Yoon, Sung-Eui
This paper presents a novel approach for reconstructing dynamic radiance fields from monocular videos. We integrate kinematics with dynamic radiance fields, bridging the gap between the sparse nature of monocular videos and the real-world physics. Ou
Externí odkaz:
http://arxiv.org/abs/2407.14059
Extending Segment Anything Model into Auditory and Temporal Dimensions for Audio-Visual Segmentation
Audio-visual segmentation (AVS) aims to segment sound sources in the video sequence, requiring a pixel-level understanding of audio-visual correspondence. As the Segment Anything Model (SAM) has strongly impacted extensive fields of dense prediction
Externí odkaz:
http://arxiv.org/abs/2406.06163
This study introduces the long-range Ising model from statistical mechanics to the Performance-Based Earthquake Engineering (PBEE) framework for regional seismic damage analysis. The application of the PBEE framework at a regional scale involves esti
Externí odkaz:
http://arxiv.org/abs/2403.11429
We present "SemCity," a 3D diffusion model for semantic scene generation in real-world outdoor environments. Most 3D diffusion models focus on generating a single object, synthetic indoor scenes, or synthetic outdoor scenes, while the generation of r
Externí odkaz:
http://arxiv.org/abs/2403.07773
RGBT multispectral pedestrian detection has emerged as a promising solution for safety-critical applications that require day/night operations. However, the modality bias problem remains unsolved as multispectral pedestrian detectors learn the statis
Externí odkaz:
http://arxiv.org/abs/2403.01300
The paper deals with the analysis of a discrete-time networked competitive bivirus susceptible-infected-susceptible (SIS) model. More specifically, we suppose that virus 1 and virus 2 are circulating in the population and are in competition with each
Externí odkaz:
http://arxiv.org/abs/2310.13853
The paper deals with the spread of two competing viruses over a network of population nodes, accounting for pairwise interactions and higher-order interactions (HOI) within and between the population nodes. We study the competitive networked bivirus
Externí odkaz:
http://arxiv.org/abs/2309.14230