Zobrazeno 1 - 10
of 12 429
pro vyhledávání: '"multi -scale feature fusion"'
With the rapid development of deep learning and computer vision technologies, medical image segmentation plays a crucial role in the early diagnosis of breast cancer. However, due to the characteristics of breast ultrasound images, such as low contra
Externí odkaz:
http://arxiv.org/abs/2412.16937
Autor:
Jin, Yuhao, Gao, Qizhong, Zhu, Xiaohui, Yue, Yong, Lim, Eng Gee, Chen, Yuqing, Wong, Prudence, Chu, Yijie
While deep learning-based robotic grasping technology has demonstrated strong adaptability, its computational complexity has also significantly increased, making it unsuitable for scenarios with high real-time requirements. Therefore, we propose a lo
Externí odkaz:
http://arxiv.org/abs/2411.12520
Publikováno v:
Telecommunication Engineering. 12/28/2024, Vol. 64 Issue 12, p1955-1962. 8p.
Autor:
Wang, Ziyi1 (AUTHOR) 20221200241@csuft.edu.cn, Huang, Wenjing2 (AUTHOR) t20142191@csuft.edu.cn, Qi, Zikang1 (AUTHOR) 20231100273@csuft.edu.cn, Yin, Shuolei1 (AUTHOR) 20231200266@csuft.edu.cn
Publikováno v:
Biomimetics (2313-7673). Dec2024, Vol. 9 Issue 12, p784. 19p.
Time series forecasting is crucial in many fields, yet current deep learning models struggle with noise, data sparsity, and capturing complex multi-scale patterns. This paper presents MFF-FTNet, a novel framework addressing these challenges by combin
Externí odkaz:
http://arxiv.org/abs/2411.17382
In multi-source remote sensing image classification field, remarkable progress has been made by convolutional neural network and Transformer. However, existing methods are still limited due to the inherent local reductive bias. Recently, Mamba-based
Externí odkaz:
http://arxiv.org/abs/2408.14255
Autor:
Zhou, Hongchao, Hu, Shunbo
In this work, we propose a novel deformable convolutional pyramid network for unsupervised image registration. Specifically, the proposed network enhances the traditional pyramid network by adding an additional shared auxiliary decoder for image pair
Externí odkaz:
http://arxiv.org/abs/2408.05717
Effective point cloud processing is crucial to LiDARbased autonomous driving systems. The capability to understand features at multiple scales is required for object detection of intelligent vehicles, where road users may appear in different sizes. R
Externí odkaz:
http://arxiv.org/abs/2409.04601
Autor:
Qin, Gang1,2,3 (AUTHOR) qingang20@mails.ucas.ac.cn, Wang, Shixin1,2,3 (AUTHOR), Wang, Futao1,2,3 (AUTHOR) wangft@aircas.ac.cn, Li, Suju2,4 (AUTHOR), Wang, Zhenqing1,2,3 (AUTHOR), Zhu, Jinfeng1,2 (AUTHOR), Liu, Ming2,4 (AUTHOR), Gu, Changjun2,4 (AUTHOR), Zhao, Qing1,2 (AUTHOR)
Publikováno v:
Remote Sensing. Nov2024, Vol. 16 Issue 22, p4328. 17p.
Autor:
Chen, Yixiong, Fang, Weichuan
In recent years, with the development of quantum machine learning, quantum neural networks (QNNs) have gained increasing attention in the field of natural language processing (NLP) and have achieved a series of promising results. However, most existi
Externí odkaz:
http://arxiv.org/abs/2405.13515