{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T16:53:16Z","timestamp":1767372796677,"version":"3.44.0"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1109\/iccp48234.2019.8959661","type":"proceedings-article","created":{"date-parts":[[2020,1,16]],"date-time":"2020-01-16T21:23:10Z","timestamp":1579209790000},"page":"499-506","source":"Crossref","is-referenced-by-count":8,"title":["Skin Lesion Diagnosis Using Deep Learning"],"prefix":"10.1109","author":[{"given":"Horea-Bogdan","family":"Mure\u015fan","sequence":"first","affiliation":[{"name":"Babe&#x015F;-Bolyai University,Faculty of Mathematics and Computer Science,Romania"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1016\/j.jid.2018.01.028"},{"doi-asserted-by":"publisher","key":"ref11","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref12","article-title":"Very deep convolutional networks for large-scale image recognition","volume":"abs 1409 1556","author":"simonyan","year":"2014","journal-title":"CoRR"},{"year":"2019","journal-title":"Dermnet Skin Disease Image Atlas","key":"ref13"},{"key":"ref14","article-title":"Imagenet large scale visual recognition challenge","volume":"abs 1409 575","author":"russakovsky","year":"2014","journal-title":"CoRR"},{"year":"2019","author":"lecun","article-title":"The mnist database of handwritten digits","key":"ref15"},{"year":"2019","author":"krizhevsky","article-title":"The cifar dataset","key":"ref16"},{"key":"ref17","article-title":"Deep residual learning for image recognition","volume":"abs 1512 3385","author":"he","year":"2015","journal-title":"CoRR"},{"key":"ref18","first-page":"1322","article-title":"Adasyn: Adaptive synthetic sampling approach for imbalanced learning","author":"he","year":"2008","journal-title":"IJCNN"},{"key":"ref19","article-title":"Going deeper with convolutions","volume":"abs 1409 4842","author":"szegedy","year":"2014","journal-title":"CoRR"},{"key":"ref4","article-title":"Skin lesion segmentation and classification with deep learning system","volume":"abs 1902 6061","author":"bisla","year":"2019","journal-title":"CoRR"},{"key":"ref3","first-page":"49","article-title":"Skin lesion classification from dermoscopic images using deep learning techniques","author":"romero lopez","year":"2017","journal-title":"2017 13th IASTED International Conference on Biomedical Engineering (BioMed) BioMed"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1038\/sdata.2018.161"},{"key":"ref5","article-title":"Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning","volume":"abs 1711 5225","author":"rajpurkar","year":"2017","journal-title":"CoRR"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1016\/j.eswa.2015.04.034"},{"key":"ref7","article-title":"Inception-v4, inception-resnet and the impact of residual connections on learning","volume":"abs 1602 7261","author":"szegedy","year":"2016","journal-title":"CoRR"},{"key":"ref2","article-title":"Skin lesions classification using convolutional neural networks in clinical images","volume":"abs 1812 2316","author":"mendes","year":"2018","journal-title":"CoRR"},{"key":"ref1","article-title":"A detection and segmentation architecture for skin lesion segmentation on dermoscopy images","volume":"abs 1809 3917","author":"qian","year":"2018","journal-title":"CoRR"},{"key":"ref9","first-page":"63","article-title":"A Color and Texture Based Hierarchical K-NN Approach to the Classification of Non-melanoma Skin Lesions","author":"ballerini","year":"2013"},{"year":"2019","journal-title":"Keras Framework","key":"ref20"},{"key":"ref21","article-title":"Evaluation: From precision, recall and f-factor to roc, informedness, markedness & correlation","volume":"2","author":"powers","year":"2008","journal-title":"Machine Learning Techniques"}],"event":{"name":"2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)","start":{"date-parts":[[2019,9,5]]},"location":"Cluj-Napoca, Romania","end":{"date-parts":[[2019,9,7]]}},"container-title":["2019 IEEE 15th International Conference on Intelligent Computer Communication and Processing (ICCP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8954839\/8959442\/08959661.pdf?arnumber=8959661","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,1]],"date-time":"2025-09-01T19:21:51Z","timestamp":1756754511000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8959661\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/iccp48234.2019.8959661","relation":{},"subject":[],"published":{"date-parts":[[2019,9]]}}}