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With the increasing integration of large lauguage models (LLMs) in education, there is growing interest in using AI agents to support student learning in creative tasks. This study presents an interactive Mentor Agent system named Mentigo, which is d
Externí odkaz:
http://arxiv.org/abs/2409.14228
Spiking neural networks (SNNs) are gaining popularity in deep learning due to their low energy budget on neuromorphic hardware. However, they still face challenges in lacking sufficient robustness to guard safety-critical applications such as autonom
Externí odkaz:
http://arxiv.org/abs/2405.20694
Spiking Neural Networks (SNNs) have attracted great attention for their energy-efficient operations and biologically inspired structures, offering potential advantages over Artificial Neural Networks (ANNs) in terms of energy efficiency and interpret
Externí odkaz:
http://arxiv.org/abs/2405.20355
Deep neural networks have demonstrated impressive success in No-Reference Image Quality Assessment (NR-IQA). However, recent researches highlight the vulnerability of NR-IQA models to subtle adversarial perturbations, leading to inconsistencies betwe
Externí odkaz:
http://arxiv.org/abs/2404.13277
The task of No-Reference Image Quality Assessment (NR-IQA) is to estimate the quality score of an input image without additional information. NR-IQA models play a crucial role in the media industry, aiding in performance evaluation and optimization g
Externí odkaz:
http://arxiv.org/abs/2403.11397
We present a learning-based approach to reconstruct buildings as 3D polygonal meshes from airborne LiDAR point clouds. What makes 3D building reconstruction from airborne LiDAR hard is the large diversity of building designs and especially roof shape
Externí odkaz:
http://arxiv.org/abs/2403.02136
Autor:
Yang, Yuzhe, Liu, Yujia, Liu, Xin, Gulhane, Avanti, Mastrodicasa, Domenico, Wu, Wei, Wang, Edward J, Sahani, Dushyant W, Patel, Shwetak
Advances in artificial intelligence (AI) have achieved expert-level performance in medical imaging applications. Notably, self-supervised vision-language foundation models can detect a broad spectrum of pathologies without relying on explicit trainin
Externí odkaz:
http://arxiv.org/abs/2402.14815
Compared to traditional Artificial Neural Network (ANN), Spiking Neural Network (SNN) has garnered widespread academic interest for its intrinsic ability to transmit information in a more energy-efficient manner. However, despite previous efforts to
Externí odkaz:
http://arxiv.org/abs/2402.00411
Autor:
Cai, Yanqing, Dang, Shijun, Yuen, Rai, Shang, Lunhua, Kou, Feifei, Yuan, Jianping, Zhang, Lei, Zhou, Zurong, Wang, Na, Li, Qingying, Wen, Zhigang, Yan, Wenming, Wang, Shuangqiang, Sun, Shengnan, Tedila, Habtamu Menberu, Xiao, Shuo, Xu, Xin, Zhao, Rushuang, Zhi, Qijun, Dong, Aijun, Zhang, Bing, Li, Wei, Ren, Yingying, Liu, Yujia
In this paper, we presented a detailed single pulse and polarization study of PSR J0614+2229 based on the archived data observed on 2019 August 15 (MJD 58710) and September 12 (MJD 58738) using the Ultra-wideband Low-frequency Receiver on the Parkes
Externí odkaz:
http://arxiv.org/abs/2401.10296