Özet
Multiple Instance Learning (MIL) has become a prominent framework for image categorization problem. In MIL framework, images are described as the combination of multiple regions. Active learning in MIL framework becomes useful when large amount of unlabeled data is available and labeling is too costly to handle for each unlabeled data. In the literature, there are some researches on MI active learning but none of them take advantage of the ensemble techniques and sparse coding. In this work, we study a Dictionary Ensemble based MI Active Learning method. Experiments show that the proposed algorithm has higher classification accuracy over other techniques.
| Tercüme edilen katkı başlığı | Dictionary ensemble based multi instance active learning method for image categorization |
|---|---|
| Orijinal dil | Türkçe |
| Ana bilgisayar yayını başlığı | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
| Yayınlayan | Institute of Electrical and Electronics Engineers Inc. |
| Sayfalar | 1221-1224 |
| Sayfa sayısı | 4 |
| ISBN (Elektronik) | 9781509016792 |
| DOI'lar | |
| Yayın durumu | Yayınlandı - 20 Haz 2016 |
| Etkinlik | 24th Signal Processing and Communication Application Conference, SIU 2016 - Zonguldak, Türkiye Süre: 16 May 2016 → 19 May 2016 |
Yayın serisi
| Adı | 2016 24th Signal Processing and Communication Application Conference, SIU 2016 - Proceedings |
|---|
???event.eventtypes.event.conference???
| ???event.eventtypes.event.conference??? | 24th Signal Processing and Communication Application Conference, SIU 2016 |
|---|---|
| Ülke/Bölge | Türkiye |
| Şehir | Zonguldak |
| Periyot | 16/05/16 → 19/05/16 |
Bibliyografik not
Publisher Copyright:© 2016 IEEE.
Keywords
- Classifier Ensemble
- Multiple-Instance Learning
- Sparse Coding
Parmak izi
Görüntü Siniflandirmasi için Sözlük Toplulugu Tabanli Çoklu Örnekli Aktif Ögrenme Metodu' araştırma başlıklarına git. Birlikte benzersiz bir parmak izi oluştururlar.Alıntı Yap
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver