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pro vyhledávání: '"Çuğu, İlke"'
Generalizing visual recognition models trained on a single distribution to unseen input distributions (i.e. domains) requires making them robust to superfluous correlations in the training set. In this work, we achieve this goal by altering the train
Externí odkaz:
http://arxiv.org/abs/2204.13091
Autor:
Cugu, Ilke, Akbas, Emre
Convolutional neural networks (CNNs) are able to attain better visual recognition performance than fully connected neural networks despite having much fewer parameters due to their parameter sharing principle. Modern architectures usually contain a s
Externí odkaz:
http://arxiv.org/abs/2102.02804
This paper is aimed at creating extremely small and fast convolutional neural networks (CNN) for the problem of facial expression recognition (FER) from frontal face images. To this end, we employed the popular knowledge distillation (KD) method and
Externí odkaz:
http://arxiv.org/abs/1711.07011
Autor:
Çuğu, İlke, Şener, Eren, Erciyes, Çağrı, Balcı, Burak, Akın, Emre, Önal, Itır, Akyüz, Ahmet Oğuz
We propose a novel tree classification system called Treelogy, that fuses deep representations with hand-crafted features obtained from leaf images to perform leaf-based plant classification. Key to this system are segmentation of the leaf from an un
Externí odkaz:
http://arxiv.org/abs/1701.08291
Akademický článek
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Autor:
Çuğu, İlke
Bilim ve mühendislikteki pek çok uygulama seyrek doğrusal sistemlerin çözümüne ihtiyaç duyar. Doğrusal sistemleri çözmenin en iyi bilinen yöntemlerinden biri onları üçgensel çarpanlarına ayırıp bu üçgensel sistemleri çözmektir.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_____10208::4f771fa27836434b8ea6104d4ede9188
https://acikbilim.yok.gov.tr/handle/20.500.12812/236635
https://acikbilim.yok.gov.tr/handle/20.500.12812/236635