Zobrazeno 1 - 10
of 148
pro vyhledávání: '"Deng, Yangdong"'
The fast-growing large scale language models are delivering unprecedented performance on almost all natural language processing tasks. However, the effectiveness of large language models are reliant on an exponentially increasing number of parameters
Externí odkaz:
http://arxiv.org/abs/2404.06709
The fast growing capabilities of large-scale deep learning models, such as Bert, GPT and ViT, are revolutionizing the landscape of NLP, CV and many other domains. Training such models, however, poses an unprecedented demand for computing power, which
Externí odkaz:
http://arxiv.org/abs/2404.07999
Autor:
Huang, Fanling, Deng, Yangdong
Publikováno v:
Data Mining and Knowledge Discovery, 2023
The prediction of wind in terms of both wind speed and direction, which has a crucial impact on many real-world applications like aviation and wind power generation, is extremely challenging due to the high stochasticity and complicated correlation i
Externí odkaz:
http://arxiv.org/abs/2309.04733
Autor:
Huang, Fanling, Deng, Yangdong
Publikováno v:
Neural Networks, 2023
Recent works have demonstrated the superiority of supervised Convolutional Neural Networks (CNNs) in learning hierarchical representations from time series data for successful classification. These methods require sufficiently large labeled data for
Externí odkaz:
http://arxiv.org/abs/2309.04732
Recent CNN based object detectors, no matter one-stage methods like YOLO, SSD, and RetinaNe or two-stage detectors like Faster R-CNN, R-FCN and FPN are usually trying to directly finetune from ImageNet pre-trained models designed for image classifica
Externí odkaz:
http://arxiv.org/abs/1804.06215
In this paper, we first investigate why typical two-stage methods are not as fast as single-stage, fast detectors like YOLO and SSD. We find that Faster R-CNN and R-FCN perform an intensive computation after or before RoI warping. Faster R-CNN involv
Externí odkaz:
http://arxiv.org/abs/1711.07264
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.