Zobrazeno 1 - 10
of 854
pro vyhledávání: '"Li Yilong"'
Publikováno v:
Redai dili, Vol 42, Iss 3, Pp 457-468 (2022)
Exploring local employment is helpful in alleviating the dualistic imbalance of employment spaces for persons with disabilities in China. Based on previous studies, customer prejudice is an important obstacle for enterprises when considering hiring p
Externí odkaz:
https://doaj.org/article/66700286e31c41c9993ebae42a34a81f
Autor:
Li, Yilong, Liu, Jingyu, Zhang, Hao, Narayanan, M Badri, Sharma, Utkarsh, Zhang, Shuai, Hu, Pan, Zeng, Yijing, Raghuram, Jayaram, Banerjee, Suman
Deploying large language models (LLMs) locally on mobile devices is advantageous in scenarios where transmitting data to remote cloud servers is either undesirable due to privacy concerns or impractical due to network connection. Recent advancements
Externí odkaz:
http://arxiv.org/abs/2410.05315
The discrete Laplacian operator holds a crucial role in 3D geometry processing, yet it is still challenging to define it on point clouds. Previous works mainly focused on constructing a local triangulation around each point to approximate the underly
Externí odkaz:
http://arxiv.org/abs/2409.06506
Integrating millimeter wave (mmWave)technology in both communication and sensing is promising as it enables the reuse of existing spectrum and infrastructure without draining resources. Most existing systems piggyback sensing onto conventional commun
Externí odkaz:
http://arxiv.org/abs/2407.04174
Publikováno v:
Dianzi Jishu Yingyong, Vol 45, Iss 1, Pp 51-54 (2019)
In order to improve the forecasting accuracy of short-term power load，a power load forecasting approach based on ensemble empirical mode decomposition(EEMD)-sample entropy(SE) and genetic algorithm(GA) for RBF neural network optimization is propose
Externí odkaz:
https://doaj.org/article/dd11777726c4422a897d6d57fc0d6662
Radar-based techniques for detecting vital signs have shown promise for continuous contactless vital sign sensing and healthcare applications. However, real-world indoor environments face significant challenges for existing vital sign monitoring syst
Externí odkaz:
http://arxiv.org/abs/2310.05507
Publikováno v:
E3S Web of Conferences, Vol 179, p 01020 (2020)
According to the current development direction in the field of information visualization, the dynamic chart is studied as the expression form of time series data, and the visualization model between data and people is established. By means of cogniti
Externí odkaz:
https://doaj.org/article/b52b99ba7ac94a2790a46556e185eda1
Autor:
Cui, Weiwei, Wang, Yaqi, Li, Yilong, Song, Dan, Zuo, Xingyong, Wang, Jiaojiao, Zhang, Yifan, Zhou, Huiyu, Chong, Bung san, Zeng, Liaoyuan, Zhang, Qianni
Accurate tooth volume segmentation is a prerequisite for computer-aided dental analysis. Deep learning-based tooth segmentation methods have achieved satisfying performances but require a large quantity of tooth data with ground truth. The dental dat
Externí odkaz:
http://arxiv.org/abs/2208.01643
Autor:
Yu, Hongjiu, Sun, Qiancheng, Hu, Jin, Xue, Xingyuan, Luo, Jixiang, He, Dailan, Li, Yilong, Wang, Pengbo, Wang, Yuanyuan, Dai, Yaxu, Wang, Yan, Qin, Hongwei
Learned image compression has achieved extraordinary rate-distortion performance in PSNR and MS-SSIM compared to traditional methods. However, it suffers from intensive computation, which is intolerable for real-world applications and leads to its li
Externí odkaz:
http://arxiv.org/abs/2207.14524
In this paper, we introduce an unsupervised cancer segmentation framework for histology images. The framework involves an effective contrastive learning scheme for extracting distinctive visual representations for segmentation. The encoder is a Deep
Externí odkaz:
http://arxiv.org/abs/2206.08791