no code implementations • 26 Dec 2023 • Zhuofu Li, Yonghong Zhang, Chengxia Wang, Shanshan Liu, Xiongkang Song, Xuquan Ji, Shuai Jiang, Woquan Zhong, Lei Hu, Weishi Li
Results: In the first stage, the average localization error of the SPU-Net algorithm for the seven key points was 0. 65mm.
no code implementations • 27 Sep 2023 • Weishi Li, Yong Peng, Miao Zhang, Liang Ding, Han Hu, Li Shen
Specifically, we categorize existing deep model fusion methods as four-fold: (1) "Mode connectivity", which connects the solutions in weight space via a path of non-increasing loss, in order to obtain better initialization for model fusion; (2) "Alignment" matches units between neural networks to create better conditions for fusion; (3) "Weight average", a classical model fusion method, averages the weights of multiple models to obtain more accurate results closer to the optimal solution; (4) "Ensemble learning" combines the outputs of diverse models, which is a foundational technique for improving the accuracy and robustness of the final model.