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20172023
most citedGMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data

39 citations · 50 across the 5 of their papers we have counts for

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5 papers

cs.CV2023

CNN-BiLSTM model for English Handwriting Recognition: Comprehensive Evaluation on the IAM Dataset

Firat Kizilirmak, Berrin Yanikoglu

We present a CNN-BiLSTM system for the problem of offline English handwriting recognition, with extensive evaluations on the public IAM dataset, including the effects of model size…

eess.IV2021★ 1 cited

COVID-19 Detection in Computed Tomography Images with 2D and 3D Approaches

Sara Atito Ali Ahmed, Mehmet Can Yavuz, Mehmet Umut Sen +9

Detecting COVID-19 in computed tomography (CT) or radiography images has been proposed as a supplement to the definitive RT-PCR test. We present a deep learning ensemble for detect…

cs.CV2020★ 2 cited

Relative Attribute Classification with Deep Rank SVM

Sara Atito Ali Ahmed, Berrin Yanikoglu

Relative attributes indicate the strength of a particular attribute between image pairs. We introduce a deep Siamese network with rank SVM loss function, called Deep Rank SVM (DRSV…

cs.LG2020★ 8 cited

Deep Convolutional Neural Network Ensembles using ECOC

Sara Atito Ali Ahmed, Cemre Zor, Berrin Yanikoglu +2

Deep neural networks have enhanced the performance of decision making systems in many applications including image understanding, and further gains can be achieved by constructing…

cs.CV2017★ 39 cited

GMM-Based Synthetic Samples for Classification of Hyperspectral Images With Limited Training Data

AmirAbbas Davari, Erchan Aptoula, Berrin Yanikoglu +2

The amount of training data that is required to train a classifier scales with the dimensionality of the feature data. In hyperspectral remote sensing, feature data can potentially…