Search Results for author: Berrin Yanikoglu

Found 10 papers, 2 papers with code

Deep Convolutional Neural Network Ensembles using ECOC

no code implementations7 Sep 2020 Sara Atito Ali Ahmed, Cemre Zor, Berrin Yanikoglu, Muhammad Awais, Josef Kittler

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 ensembles.

Decision Making

Relative Attribute Classification with Deep Rank SVM

no code implementations9 Sep 2020 Sara Atito Ali Ahmed, Berrin Yanikoglu

Relative attributes indicate the strength of a particular attribute between image pairs.

Attribute Classification +1

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

no code implementations16 May 2021 Sara Atito Ali Ahmed, Mehmet Can Yavuz, Mehmet Umut Sen, Fatih Gulsen, Onur Tutar, Bora Korkmazer, Cesur Samanci, Sabri Sirolu, Rauf Hamid, Ali Ergun Eryurekli, Toghrul Mammadov, Berrin Yanikoglu

The 2D system detects the infection on each CT slice independently, combining them to obtain the patient-level decision via different methods (averaging and long-short term memory networks).

Computed Tomography (CT)

Real or Virtual: A Video Conferencing Background Manipulation-Detection System

no code implementations25 Apr 2022 Ehsan Nowroozi, Yassine Mekdad, Mauro Conti, Simone Milani, Selcuk Uluagac, Berrin Yanikoglu

Additionally, it enables users to employ a virtual background to conceal their own environment due to privacy concerns or to reduce distractions, particularly in professional settings.

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

no code implementations2 Jul 2023 Firat Kizilirmak, Berrin Yanikoglu

Test time augmentation with rotation and shear transformations applied to the input image, is proposed to increase recognition of difficult cases and found to reduce the word error rate by 2. 5\% points.

Data Augmentation Handwriting Recognition

Variational Self-Supervised Contrastive Learning Using Beta Divergence For Face Understanding

1 code implementation5 Sep 2023 Mehmet Can Yavuz, Berrin Yanikoglu

The method (VCL) utilizes variational contrastive learning with beta-divergence to learn robustly from unlabelled datasets, including uncurated and noisy datasets.

Face Recognition Self-Supervised Learning

Semantic Similarity Based Evaluation for Abstractive News Summarization

1 code implementation ACL (GEM) 2021 Figen Beken Fikri, Kemal Oflazer, Berrin Yanikoglu

To achieve this, we translated the English STSb dataset into Turkish and presented the first semantic textual similarity dataset for Turkish as well.

Abstractive Text Summarization News Summarization +2

A Turkish Hate Speech Dataset and Detection System

no code implementations LREC 2022 Fatih Beyhan, Buse Çarık, İnanç Arın, Ayşecan Terzioğlu, Berrin Yanikoglu, Reyyan Yeniterzi

We present a machine learning system for automatic detection of hate speech in Turkish, along with a hate speech dataset consisting of tweets collected in two separate domains.

Binary Classification Hate Speech Detection

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