Efficient asynchronous federated learning with sparsification and quantization
While data is distributed in multiple edge devices, federated learning (FL) is attracting more
and more attention to collaboratively train a machine learning model without transferring raw …
and more attention to collaboratively train a machine learning model without transferring raw …
Relation Modeling and Distillation for Learning with Noisy Labels
X Che, J Zhang, Z Qi, X Qi - arXiv preprint arXiv:2405.19606, 2024 - arxiv.org
Learning with noisy labels has become an effective strategy for enhancing the robustness of
models, which enables models to better tolerate inaccurate data. Existing methods either …
models, which enables models to better tolerate inaccurate data. Existing methods either …
Tomato ripeness detection based on image recognition
X Liu - International Conference on Image, Signal Processing …, 2024 - spiedigitallibrary.org
With the improvement of people's living standard, shopping has become more and more
people's preference. When buying a product, one of the most important factors is how it …
people's preference. When buying a product, one of the most important factors is how it …