Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-end training of a two-stage neural network for defect detection   Segmentation-based, two-stage neural network has shown excellent results in
the surface defect detection, enabling the network to learn from a relatively
small number of samples. In this work, we introduce end-to-end training of the
two-stage network together with several extensions to the training process,
which reduce the amount of training time and improve the results on the surface
defect detection tasks. To enable end-to-end training we carefully balance the
contributions of both the segmentation and the classification loss throughout
the learning. We adjust the gradient flow from the classification into the
segmentation network in order to prevent the unstable features from corrupting
the learning. As an additional extension to the learning, we propose
frequency-of-use sampling scheme of negative samples to address the issue of
over- and under-sampling of images during the training, while we employ the
distance transform algorithm on the region-based segmentation masks as weights
for positive pixels, giving greater importance to areas with higher probability
of presence of defect without requiring a detailed annotation. We demonstrate
the performance of the end-to-end training scheme and the proposed extensions
on three defect detection datasets - DAGM, KolektorSDD and Severstal Steel
defect dataset - where we show state-of-the-art results. On the DAGM and the
KolektorSDD we demonstrate 100\% detection rate, therefore completely solving
the datasets. Additional ablation study performed on all three datasets
quantitatively demonstrates the contribution to the overall result improvements
for each of the proposed extensions.

36
The categories of this paper are: cmp-lg
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
20
The categories of this paper are: acc-phys
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an