Zobrazeno 1 - 10
of 2 391
pro vyhledávání: '"Zhang, JinCheng"'
To facilitate the re-identification (re-ID) of individual animals, existing methods primarily focus on maximizing feature similarity within the same individual and enhancing distinctiveness between different individuals. However, most of them still r
Externí odkaz:
http://arxiv.org/abs/2405.00468
Manual identification of archaeological features in LiDAR imagery is labor-intensive, costly, and requires archaeological expertise. This paper shows how recent advancements in deep learning (DL) present efficient solutions for accurately segmenting
Externí odkaz:
http://arxiv.org/abs/2403.05773
Polarization engineering has been proven to enhance the capabilities of light manipulation and thus facilitate the development of integrated photonic devices. In this study, we introduce a polarization rotator based on gradiently-twisted $\alpha$-MoO
Externí odkaz:
http://arxiv.org/abs/2403.01122
Tunable optical filter at the chip scale plays a crucial role in fulfilling the need for the reconfigurability in channel routing, optical switching, and wavelength division multiplexing systems. In this letter, we propose a tunable double notch filt
Externí odkaz:
http://arxiv.org/abs/2403.01115
Publikováno v:
SoutheastCon 2024, 559-564
This paper describes the hardware design and flight demonstration of a small quadrotor with imaging sensors for urban mapping, hazard avoidance, and target tracking research. The vehicle is equipped with five cameras, including two pairs of fisheye s
Externí odkaz:
http://arxiv.org/abs/2402.13195
Publikováno v:
Sensors 24, no. 7: 2204
This article presents an analysis of current state-of-the-art sensors and how these sensors work with several mapping algorithms for UAV (Unmanned Aerial Vehicle) applications, focusing on low-altitude and high-speed scenarios. A new experimental con
Externí odkaz:
http://arxiv.org/abs/2401.06407
Deploying end-to-end speech recognition models with limited computing resources remains challenging, despite their impressive performance. Given the gradual increase in model size and the wide range of model applications, selectively executing model
Externí odkaz:
http://arxiv.org/abs/2401.02046
Wake effects, i.e. the reduced momentum and increased turbulence caused by the upstream wind farm, have a significant adverse impact on downstream wind farms. However, due to the lack of ground truth for flow scenarios without wind farms in place (as
Externí odkaz:
http://arxiv.org/abs/2312.13942
Emerging Denoising Diffusion Probabilistic Models (DDPM) have become increasingly utilised because of promising results they have achieved in diverse generative tasks with continuous data, such as image and sound synthesis. Nonetheless, the success o
Externí odkaz:
http://arxiv.org/abs/2310.14044
Diffusion models have shown promising results for a wide range of generative tasks with continuous data, such as image and audio synthesis. However, little progress has been made on using diffusion models to generate discrete symbolic music because t
Externí odkaz:
http://arxiv.org/abs/2310.14040