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"LibFewShot: A Comprehensive Library for Few-Shot Learning" by Wenbin Li, Ziyi Wang et al.

Few-shot learning, especially few-shot image classification, has received increasing attention and witnessed significant advances in recent years. Some recent studies implicitly show that many generic techniques or โ€œtricksโ€, such as data augmentation, pre-training, knowledge distillation, and self-supervision, may greatly boost the performance of a few-shot learning method. Moreover, different works may employ different software platforms, backbone architectures and input image sizes, making...
Benchmark Testing Deep Learning Hair Comparison Few Shot Learning Image Classification Task Analysis
Source: uow.edu.au

"Health Monitoring of Old Buildings in Bangladesh: Detection of Cracks " by Rafiul Bari Angan, Md Safaiat Hossain et al.

Numerous buildings in Bangladesh were constructed without following standard building codes. As a result, those are vulnerable to increased earthquake frequency and variable loads. To address this issue, old buildings need to be monitored frequently by non-destructive testing (NDT) to avoid any failures. The identification of cracks and dampness is one of the most important parts of this test. Generally, this detection part is costly and time-consuming to conduct it manually. To resolve this, th...
Convolutional Neural Network Average Precision Crack And Dampness Deep Learning Deep Neural Network Dnn Object Detection
Source: uow.edu.au

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