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pro vyhledávání: '"Tang, Sheyang"'
Mesh quality assessment (MQA) models play a critical role in the design, optimization, and evaluation of mesh operation systems in a wide variety of applications. Current MQA models, whether model-based methods using topology-aware features or projec
Externí odkaz:
http://arxiv.org/abs/2412.01986
Autor:
Karmani, Sachin, Sivakaran, Thanushon, Prasad, Gaurav, Ali, Mehmet, Yang, Wenbo, Tang, Sheyang
Publikováno v:
2024 IEEE 26th International Workshop on Multimedia Signal Processing (MMSP)
Deep learning models often function as black boxes, providing no straightforward reasoning for their predictions. This is particularly true for computer vision models, which process tensors of pixel values to generate outcomes in tasks such as image
Externí odkaz:
http://arxiv.org/abs/2410.00267
Autor:
Tang, Sheyang, Hosseini, Mahdi S., Chen, Lina, Varma, Sonal, Rowsell, Corwyn, Damaskinos, Savvas, Plataniotis, Konstantinos N., Wang, Zhou
AI technology has made remarkable achievements in computational pathology (CPath), especially with the help of deep neural networks. However, the network performance is highly related to architecture design, which commonly requires human experts with
Externí odkaz:
http://arxiv.org/abs/2108.06859
Recent years have witnessed the rapid proliferation of backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes. Localizing such backscatter tags is crucial for IoT-based smart applicatio
Externí odkaz:
http://arxiv.org/abs/2005.13534
Recent years have witnessed the rapid proliferation of low-power backscatter technologies that realize the ubiquitous and long-term connectivity to empower smart cities and smart homes. Localizing such low-power backscatter tags is crucial for IoT-ba
Externí odkaz:
http://arxiv.org/abs/1908.03297
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