Zobrazeno 1 - 10
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pro vyhledávání: '"Chen, Junyi"'
Autor:
Ma, Yuqi, Zhao, Ziming, Zhang, Wenkang, Lv, Jianfeng, Chen, Junyi, Yan, Xueqin, Lin, XiaoJi, Zhang, Junlong, Wang, Bingwu, Gao, Song, Xiao, Jie, Yang, Gen
FLASH radiotherapy (FLASH-RT) is a new modality of radiotherapy by delivering doses with ultra-high dose rates. FLASH-RT has the ability to suppress tumor growth while sparing normal tissues, known as the FLASH effect. Although FLASH effect has prove
Externí odkaz:
http://arxiv.org/abs/2405.10219
Autor:
He, Xianglong, Chen, Junyi, Peng, Sida, Huang, Di, Li, Yangguang, Huang, Xiaoshui, Yuan, Chun, Ouyang, Wanli, He, Tong
In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel diffusion-based
Externí odkaz:
http://arxiv.org/abs/2403.12957
Autor:
Chen, Junyi
In recent years, Recommender Systems(RS) have witnessed a transformative shift with the advent of Large Language Models(LLMs) in the field of Natural Language Processing(NLP). These models such as OpenAI's GPT-3.5/4, Llama from Meta, have demonstrate
Externí odkaz:
http://arxiv.org/abs/2311.12338
Autor:
Yang, Jianlei, Liao, Jiacheng, Lei, Fanding, Liu, Meichen, Chen, Junyi, Long, Lingkun, Wan, Han, Yu, Bei, Zhao, Weisheng
Developing deep learning models on tiny devices (e.g. Microcontroller units, MCUs) has attracted much attention in various embedded IoT applications. However, it is challenging to efficiently design and deploy recent advanced models (e.g. transformer
Externí odkaz:
http://arxiv.org/abs/2311.01759
Autor:
Chen, Junyi
Polysaccharides are known as among the most abundant natural polymers on the Earth. As this class of material is usually renewable, biodegradable, biocompatible in many contexts and environmentally friendly, it is of great interest to use these benig
Externí odkaz:
http://hdl.handle.net/10919/111396
Autonomous vehicles are exposed to various weather during operation, which is likely to trigger the performance limitations of the perception system, leading to the safety of the intended functionality (SOTIF) problems. To efficiently generate data f
Externí odkaz:
http://arxiv.org/abs/2309.02964
Building scalable vision-language models to learn from diverse, multimodal data remains an open challenge. In this paper, we introduce an Efficient Vision-languagE foundation model, namely EVE, which is one unified multimodal Transformer pre-trained
Externí odkaz:
http://arxiv.org/abs/2308.11971
Autor:
Ma, Yining, Jiang, Wei, Zhang, Lingtong, Chen, Junyi, Wang, Hong, Lv, Chen, Wang, Xuesong, Xiong, Lu
Interaction between the background vehicles (BVs) and automated vehicles (AVs) in scenario-based testing plays a critical role in evaluating the intelligence of the AVs. Current testing scenarios typically employ predefined or scripted BVs, which ina
Externí odkaz:
http://arxiv.org/abs/2306.07142
Autor:
Zhang, Zhihao, Luo, Siwen, Chen, Junyi, Lai, Sijia, Long, Siqu, Chung, Hyunsuk, Han, Soyeon Caren
We propose a PiggyBack, a Visual Question Answering platform that allows users to apply the state-of-the-art visual-language pretrained models easily. The PiggyBack supports the full stack of visual question answering tasks, specifically data process
Externí odkaz:
http://arxiv.org/abs/2211.15940
The autonomous vehicle (AV) is a safety-critical system relying on complex sensors and algorithms. The AV may confront risk conditions if these sensors and algorithms misunderstand the environment and situation, even though all components are fault-f
Externí odkaz:
http://arxiv.org/abs/2210.08724