4 citations · 10 across the 3 of their papers we have counts for
4 papers
Pushing the Envelope of Thin Crack Detection
Liang Xu, Taro Hatsutani, Xing Liu +3
In this study, we consider the problem of detecting cracks from the image of a concrete surface for automated inspection of infrastructure, such as bridges. Its overall accuracy is…
Bridging In- and Out-of-distribution Samples for Their Better Discriminability
Engkarat Techapanurak, Anh-Chuong Dang, Takayuki Okatani
This paper proposes a method for OOD detection. Questioning the premise of previous studies that ID and OOD samples are separated distinctly, we consider samples lying in the inter…
Practical Evaluation of Out-of-Distribution Detection Methods for Image Classification
Engkarat Techapanurak, Takayuki Okatani
We reconsider the evaluation of OOD detection methods for image recognition. Although many studies have been conducted so far to build better OOD detection methods, most of them fo…
Hyperparameter-Free Out-of-Distribution Detection Using Softmax of Scaled Cosine Similarity
Engkarat Techapanurak, Masanori Suganuma, Takayuki Okatani
The ability to detect out-of-distribution (OOD) samples is vital to secure the reliability of deep neural networks in real-world applications. Considering the nature of OOD samples…