Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Self-paced learning to improve text row detection in historical
  documents with missing labels   An important preliminary step of optical character recognition systems is the
detection of text rows. To address this task in the context of historical data
with missing labels, we propose a self-paced learning algorithm capable of
improving the row detection performance. We conjecture that pages with more
ground-truth bounding boxes are less likely to have missing annotations. Based
on this hypothesis, we sort the training examples in descending order with
respect to the number of ground-truth bounding boxes, and organize them into k
batches. Using our self-paced learning method, we train a row detector over k
iterations, progressively adding batches with less ground-truth annotations. At
each iteration, we combine the ground-truth bounding boxes with pseudo-bounding
boxes (bounding boxes predicted by the model itself) using non-maximum
suppression, and we include the resulting annotations at the next training
iteration. We demonstrate that our self-paced learning strategy brings
significant performance gains on two data sets of historical documents,
improving the average precision of YOLOv4 with more than 12% on one data set
and 39% on the other.

22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
30
The categories of this paper are: q-alg
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin