Yali Nie

Doktorand|Doctoral Student

  • Professional title: Doctoral Student
  • Department: Department of Electronics Design (EKS)
  • Telephone: +46 (0)10-1427819
  • Email: yali.nie@miun.se
  • Room number: S225
  • Location: Sundsvall
  • Employee in the subject: Computer Science, Electrical Engineering

Publications

Conference

Publications

Articles in journals

Nie, Y. , Sommella, P. , Carratu, M. , Ferro, M. , O'Nils, M. & Lundgren, J. (2022). Recent Advances in Diagnosis of Skin Lesions using Dermoscopic Images based on Deep Learning. IEEE Access,  

Conference papers

Nie, Y. , Carratu, M. , O'Nils, M. , Sommella, P. , Moise, A. U. & Lundgren, J. (2022). Skin Cancer Classification based on Cosine Cyclical Learning Rate with Deep Learning. In Conference Record - IEEE Instrumentation and Measurement Technology Conference.  

Nie, Y. , Ferro, M. , Sommella, P. , Carratù, M. , Cacciapuoti, S. , Di Leo, G. , Lundgren, J. & Fabbrocini, G. (2021). Ensembling CNNs for dermoscopic analysis of suspicious skin lesions. In 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA).  

Nie, Y. , De Santis, L. , Carratu, M. , O'Nils, M. , Sommella, P. & Lundgren, J. (2020). Deep Melanoma classification with K-Fold Cross-Validation for Process optimization. In 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA).  

Nie, Y. , Sommella, P. , O'Nils, M. , Liguori, C. & Lundgren, J. (2019). Automatic Detection of Melanoma with Yolo Deep Convolutional Neural Networks. In 2019 E-Health and Bioengineering Conference (EHB).    

Licentiate theses, comprehensive summaries

Nie, Y. (2021). Automatic Melanoma Diagnosis in Dermoscopic Imaging Base on Deep Learning System. Lic. (Comprehensive summary) Mid Sweden University, 2021 (Mid Sweden University licentiate thesis : 180)  

The page was updated 5/7/2021