Deep Transfer Learning

Deep Transfer Learning

We study transfer learning, which aims to adapt previously gained knowledge to small scale problems. Transfer from very deep architectures may cause overfitting. We investigate CNN pruning for transfer.

Poster: https://drive.google.com/file/d/1b3BOGx4UQ2dr_lva4kCAFhGylEX4K82a/view?usp=sharing

Video: https://drive.google.com/file/d/1Sau94hldTGY0aaR7DUaEQdI4Ye72RJ5p/view?usp=sharing

 

Project Poster: 

Project Members: 

Furkan Kadıoğlu

Project Advisor: 

İnci Meliha Baytaş

Project Status: 

Project Year: 

2020
  • Spring

Bize Ulaşın

Bilgisayar Mühendisliği Bölümü, Boğaziçi Üniversitesi,
34342 Bebek, İstanbul, Türkiye

  • Telefon: +90 212 359 45 23/24
  • Faks: +90 212 2872461
 

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