Zobrazeno 1 - 10
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pro vyhledávání: '"Li, Bingbing"'
Driver action recognition, aiming to accurately identify drivers' behaviours, is crucial for enhancing driver-vehicle interactions and ensuring driving safety. Unlike general action recognition, drivers' environments are often challenging, being gloo
Externí odkaz:
http://arxiv.org/abs/2408.01766
Learning-based intelligent energy management systems for plug-in hybrid electric vehicles (PHEVs) are crucial for achieving efficient energy utilization. However, their application faces system reliability challenges in the real world, which prevents
Externí odkaz:
http://arxiv.org/abs/2406.09082
Autor:
Ma, Jiaheng, Wang, Chengyuan, Li, Bingbing, Chen, Yun, Yang, Ye, Wang, Jinwen, Yang, Xin, Qiu, Shuwei, Gao, Hong, Li, Fuli
Publikováno v:
Optics Express 32, 23026-23035 (2024)
Orbital angular momentum (OAM) entangled photon pairs with narrow bandwidths play a crucial role in the interaction of light and quantum states of matter. In this article, we demonstrate an approach for generating OAM entangled photon pairs with a na
Externí odkaz:
http://arxiv.org/abs/2405.20570
Autor:
Wang, Huadeng, Yu, Jiejiang, Li, Bingbing, Pan, Xipeng, Liu, Zhenbing, Lan, Rushi, Luo, Xiaonan
Publikováno v:
ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Republic of, 2024, pp. 2345-2349
Accurate and automated gland segmentation on pathological images can assist pathologists in diagnosing the malignancy of colorectal adenocarcinoma. However, due to various gland shapes, severe deformation of malignant glands, and overlapping adhesion
Externí odkaz:
http://arxiv.org/abs/2401.15990
Autor:
Lin, Dan, Lee, Philip Hann Yung, Li, Yiming, Wang, Ruoyu, Yap, Kim-Hui, Li, Bingbing, Ngim, You Shing
Driver Action Recognition (DAR) is crucial in vehicle cabin monitoring systems. In real-world applications, it is common for vehicle cabins to be equipped with cameras featuring different modalities. However, multi-modality fusion strategies for the
Externí odkaz:
http://arxiv.org/abs/2401.14838
Autor:
Li, Bingbing, Yuan, Geng, Wang, Zigeng, Huang, Shaoyi, Peng, Hongwu, Behnam, Payman, Wen, Wujie, Liu, Hang, Ding, Caiwen
Resistive Random Access Memory (ReRAM) has emerged as a promising platform for deep neural networks (DNNs) due to its support for parallel in-situ matrix-vector multiplication. However, hardware failures, such as stuck-at-fault defects, can result in
Externí odkaz:
http://arxiv.org/abs/2401.11664
Autor:
Wang, Hao, Lin, Jiatai, Li, Danyi, Wang, Jing, Zhao, Bingchao, Shi, Zhenwei, Pan, Xipeng, Wang, Huadeng, Li, Bingbing, Liang, Changhong, Han, Guoqiang, Liang, Li, Han, Chu, Liu, Zaiyi
Mitosis detection is one of the fundamental tasks in computational pathology, which is extremely challenging due to the heterogeneity of mitotic cell. Most of the current studies solve the heterogeneity in the technical aspect by increasing the model
Externí odkaz:
http://arxiv.org/abs/2307.05889
Generative chat models, such as ChatGPT and GPT-4, have revolutionized natural language generation (NLG) by incorporating instructions and human feedback to achieve significant performance improvements. However, the lack of standardized evaluation be
Externí odkaz:
http://arxiv.org/abs/2305.14471
Mitosis detection is one of the challenging problems in computational pathology, and mitotic count is an important index of cancer grading for pathologists. However, current counts of mitotic nuclei rely on pathologists looking microscopically at the
Externí odkaz:
http://arxiv.org/abs/2301.07627