TY  - JOUR
T1  - AZ ATIŞLI ÖĞRENME: SAĞLIK VE TARIM ALANINDA UYGULAMALARIN İNCELENMESİ
TT  - FEW-SHOT LEARNING: REVIEW OF APPLICATIONS IN HEALTH AND AGRICULTURE
AU  - Vargün, Emine
PY  - 2025
DA  - June
Y2  - 2025
JF  - Yönetim Bilişim Sistemleri Dergisi
PB  - Dokuz Eylül Üniversitesi
WT  - DergiPark
SN  - 2630-550X
SP  - 18
EP  - 30
VL  - 11
IS  - 1
LA  - tr
AB  - Few-Shot Learning (FSL), sınırlı veriyle yüksek doğruluk elde etmeyi hedefleyen yenilikçi bir makine öğrenimi yöntemidir. Bu çalışmada, FSL'nin veri toplamanın zor ve maliyetli olduğu sağlık ve tarım alanındaki uygulamaları ele alınmaktadır. Sağlık sektöründe cilt kanseri teşhisi ve göz hastalıklarının tanısında FSL, az veri ile yüksek doğruluk sağlamaktadır. Tarım sektöründe ise bitki hastalıklarının erken teşhisinde kullanılarak ürün verimliliğini artırmaktadır. Çalışma, FSL’nin meta-öğrenme, aktarım öğrenmesi ve benzerlik tabanlı tekniklerini inceleyerek veri kısıtlılığına karşı sunduğu avantajları ve gelecekteki uygulama potansiyelini değerlendirmektedir.
KW  - Few-Shot Learning
KW  - Meta-öğrenme
KW  - Aktarım öğrenmesi
KW  - Benzerlik tabanlı öğrenme
KW  - Veri kısıtlılığı
KW  - Tıbbi görüntüleme
KW  - Bitki hastalığı tanısı
KW  - Cilt kanseri teşhisi
KW  - Tarım uygulamaları
KW  - Sağlık uygulamaları
N2  - Few-Shot Learning (FSL) is an innovative machine learning method that aims to achieve high accuracy with limited data. In this study, we focus on the applications of FSL in healthcare and agriculture, where data collection is difficult and costly. In the health sector, FSL provides high accuracy with little data in skin cancer diagnosis and eye disease diagnosis. In the agriculture sector, it is used in the early diagnosis of plant diseases to increase crop productivity. The study examines FSL's meta-learning, transfer learning and similarity-based techniques to assess its advantages over data constraints and its potential for future applications.
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UR  - https://dergipark.org.tr/tr/pub/ybs/issue//1603989
L1  - https://dergipark.org.tr/tr/download/article-file/4451923
ER  -