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In recent years, the data-driven approach has emerged as the predominant method for estimating the Remaining Useful Life (RUL) of bearings. This approach offers notable advantages, including reduced reliance on expert knowledge in bearing health analysis. However, there are three significant drawbacks associated with data-driven models that have impeded the advancement of bearing RUL estimation. These drawbacks encompass limited data availability, constrained model generalization ability, and inadequate adaptability to the nonlinear degradation process of bearings. To address these limitations...

A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization - GitHub - continuousml/Awesome-Out-Of-Distribution-Detection: A professionally curated list of papers, tutorials, books, videos, articles and open-source libraries etc for Out-of-distribution detection, robustness, and generalization

As for few-shot image classification, recently, some works revisit the standard transfer learning paradigm, i.e., pre-training and fine-tuning, and have achieved some success. However, we find that this kind of methods heavily relies on a naive image-level data augmentation (e.g., cropping and flipping) at the fine-tuning stage, which will easily suffer from the overfitting problem because of the limited-data regime. To tackle this issue, in this paper, we attempt to perform a novel feature-level semantic augmentation at the fine-tuning stage and propose a Global- and Local-aware Feature Augme...

A deep dive into Transformer a neural network architecture that was introduced in the famous paper “attention is all you need” in 2017, its applications, impacts, challenges and future directions

/PRNewswire/ -- The "Composite AI Market by Offering (Software, Hardware, Services), Technique (Data Processing, Pattern Recognition), Application (Product...