title={Mean Teacher-based Cross-Domain Activity Recognition using WiFi Signals}, year={2023}, volume={10}, number={14}, pages={12787-12797}, doi={10.1109/JIOT.2023.3256324} } The two public datasets used in the paper are shown below. ...
While training together in the traditional mean teacher framework, the teacher model and the student model share the same structure. An Exponential Moving Average (EMA) updating strategy is applied to optimize the teacher model. Although the EMA approach facilitates a smooth training process, it ...
Furthermore, an Adaptive Mean Teacher approach was developed based on the Mean Teacher to enhance the effectiveness of semi-supervised cell segmentation. Regarding the signal point detection task, an end-to-end semi-supervised signal point detection algorithm was developed using the Adaptive Mean ...
1.1.1. Mean Teacher Learning Mean teacher learning is a semi-supervised paradigm based on the interaction between two models referred to as the teacher model and the student model. In the first place, Samuli et al. [20] proposed a novel architecture in which the temporal ensembling maintains ...
The median sales price of these houses was $150,000 and the average (arithmetic mean) sales price was $200,000. The sales price of the most expensive house was at least three times the sales price of the least expensive house. Based on the information provided, what is the minimum ...
(CPR). For CPR, ideal compression depth is 40 to 50 millimeters (mm). The children used a practice mannequin with sensors that recorded the average (arithmetic mean) depth achieved by each child. The results are plotted on the graph.Based on the information provided, select from each drop-...
Subsequently, we leverage the mean teacher model to simultaneously learn from labeled and unlabeled inputs alongside orthogonal view representations, enabling our approach to harness all available annotations. Our network can improve the learning ability and attain superior performance. Extensiv...
We build on a keypoint-based registration model, combining graph convolutions for geometric feature learning with loopy belief optimization, and propose to reduce the domain shift through self-ensembling. To this end, we embed the model into the Mean Teacher paradigm. We extend the Mean Teacher ...
Performance analysis of weakly-supervised sound event detection system based on the mean-teacher convolutional recurrent neural network modeldoi:10.7776/ASK.2021.40.2.139Seok Jin LeeThe Acoustical Society of Korea
To mitigate the impact of error-prone pseudo-labels, we propose a mutual mean teacher framework for cross-domain aspect-based sentiment analysis. This framework generates pseudo-labels using a peer teacher network, thereby providing more reliable and robust pseudo-labels. Additionally, to develop a ...