Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Two-phase training mitigates class imbalance for camera trap image
  classification with CNNs   By leveraging deep learning to automatically classify camera trap images,
ecologists can monitor biodiversity conservation efforts and the effects of
climate change on ecosystems more efficiently. Due to the imbalanced
class-distribution of camera trap datasets, current models are biased towards
the majority classes. As a result, they obtain good performance for a few
majority classes but poor performance for many minority classes. We used
two-phase training to increase the performance for these minority classes. We
trained, next to a baseline model, four models that implemented a different
versions of two-phase training on a subset of the highly imbalanced Snapshot
Serengeti dataset. Our results suggest that two-phase training can improve
performance for many minority classes, with limited loss in performance for the
other classes. We find that two-phase training based on majority undersampling
increases class-specific F1-scores up to 3.0%. We also find that two-phase
training outperforms using only oversampling or undersampling by 6.1% in
F1-score on average. Finally, we find that a combination of over- and
undersampling leads to a better performance than using them individually.

28
The categories of this paper are: alg-geom
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg