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Over the years utilities have accumulated a large number of measured FRA data whilst the transformers' design information such as winding types may or may not necessarily be known. Different winding types own different equivalent electrical parameters, i.e. capacitance and inductance. For instance, ...
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the methods c
This approach uses transformers and CNNs to complement their model and achieves 87.1%87.1% using ImageNet-1k [25]. Another natural color image approach is described in [26]. In this approach, the image is split into patches that feed the embedding module to expand the feature dimensions used...
As a transformer-based approach, BERT (Bidirectional Encoder Representations from Transformers) [34] has achieved amazing results in many language understanding tasks, including the tasks of text classification. However, those advanced models usually have a large size with many parameters, making a ...
Bidirectional Encoder Representations from Transformers (BERT)To tackle this task, we also can leverage transfer learning tech and the idea of multi-task learning we just learned. BERT is a transformer encoder and also a language representation model. Unlike other language representation models, BERT ...