Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid
  Pooling Networks   Skin lesion segmentation (SLS) in dermoscopic images is a crucial task for
automated diagnosis of melanoma. In this paper, we present a robust deep
learning SLS model, so-called SLSDeep, which is represented as an
encoder-decoder network. The encoder network is constructed by dilated residual
layers, in turn, a pyramid pooling network followed by three convolution layers
is used for the decoder. Unlike the traditional methods employing a
cross-entropy loss, we investigated a loss function by combining both Negative
Log Likelihood (NLL) and End Point Error (EPE) to accurately segment the
melanoma regions with sharp boundaries. The robustness of the proposed model
was evaluated on two public databases: ISBI 2016 and 2017 for skin lesion
analysis towards melanoma detection challenge. The proposed model outperforms
the state-of-the-art methods in terms of segmentation accuracy. Moreover, it is
capable to segment more than $100$ images of size 384x384 per second on a
recent GPU.

16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
31
The categories of this paper are: ao-sci
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
7
The categories of this paper are: hep-th