Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning to Detect Blue-white Structures in Dermoscopy Images with Weak
  Supervision   We propose a novel approach to identify one of the most significant
dermoscopic criteria in the diagnosis of Cutaneous Melanoma: the Blue-whitish
structure. In this paper, we achieve this goal in a Multiple Instance Learning
framework using only image-level labels of whether the feature is present or
not. As the output, we predict the image classification label and as well
localize the feature in the image. Experiments are conducted on a challenging
dataset with results outperforming state-of-the-art. This study provides an
improvement on the scope of modelling for computerized image analysis of skin
lesions, in particular in that it puts forward a framework for identification
of dermoscopic local features from weakly-labelled data.

26
The categories of this paper are: bayes-an
14
The categories of this paper are: math-ph
29
The categories of this paper are: funct-an
19
The categories of this paper are: eess
15
The categories of this paper are: nucl-ex
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
30
The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys