Gözde Akar

E-mail

bozdagi@metu.edu.tr

Department

Department of Electrical and Electronics Engineering

ORCID

0000-0002-4227-5606

Scopus Author ID

55662888100

Web of Science Researcher ID

AAZ-8753-2020

Cross-Modal Learning via Adversarial Loss and Covariate Shift for Enhanced Liver Segmentation Ozkan, Savas; SELVER, MUSTAFA ALPER; Baydar, Bora; Kavur, Ali Emre; Candemir, Cemre; Akar, Gözde (2024-01-01) Despite the widespread use of deep learning methods for semantic segmentation from single imaging modalities, their performance for exploiting multi-domain data still needs to improve. However, the decision-making process ...
PULSE: A DL-assisted physics-based approach to the inverse problem of electrocardiography Ugurlu, Kutay; Akar, Gözde; Serinağaoğlu Doğrusöz, Yeşim (2024-01-01) This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reco...
Crowd Multi Prediction: Single Network for Crowd Counting, Localization and Anomaly Detection Coskun, Muhammet Furkan; Akar, Gözde (2023-01-01) In this study, we propose a neural network to solve crowd counting, localization and abnormal event detection problems together. Our proposed model combines P2P-Net with a novel crowd anomaly detection module. The final ne...
SSIM Modelin Geliştirilmesine Dayanan Bir 3B Video Kalite Değerlendirme Metriği Yılmaz, Gökçe Nur; Akar, Gözde (2022-02-01) Günümüzdeki en revaçta araştırma alanlarından birisi kullanıcılara gelişmiş çoklu-ortam servisleri sağlayabilmek adına 3 Boyutlu (3B) video Kalite Deneyimini (KD) etkin olarak tahmin eden objektif metriklerin geliştirilmes...
The Effect of Virtual Reality and Prediction in Visual Field Test Görme Alani Testinde Sanal Gerçeklik ve Öngörmenin Etkisi Bulbul, Emre; Akar, Gözde (2022-01-01) Visual field testing is the gold standard for evaluating a patient's visual field. Visual field testing is required for monitoring and diagnosis of several disorders, including glaucoma, which affects more than 80 million ...
CHAOS Challenge- combined (CT-MR) healthy abdominal organ segmentation Kavur, A. Emre; et. al. (2021-04-01) Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation system...
VISIBLE AND INFRARED IMAGE FUSION USING ENCODER-DECODER NETWORK Ataman, Ferhat Can; Akar, Gözde (2021-01-01) © 2021 IEEE.The aim of multispectral image fusion is to combine object or scene features of images with different spectral characteristics to increase the perceptual quality. In this paper, we present a novel learning-base...
Exploiting Local Indexing and Deep Feature Confidence Scores for Fast Image-to-Video Search Ozkan, Savas; Akar, Gözde (2021-01-01) The cost-effective visual representation and fast query-by-example search are two challenging goals that should be maintained for web-scale visual retrieval tasks on moderate hardware. This paper introduces a fast and robu...
Dental X-ray Image Segmentation using Octave Convolution Neural Network Kaya, Mete Can; Akar, Gözde (2020-01-01) In this paper, we present a Unet architecture made of octave convolution for dental image segmentation problem. In this architecture, the requirements for memory and accuracy are significantly improved compared to previous...
Comparison of semi-automatic and deep learning-based automatic methods for liver segmentation in living liver transplant donors Kavur, A. Emre; GEZER, NACİYE SİNEM; Baris, Mustafa; Sahin, Yusuf; Ozkan, Savas; Baydar, Bora; Yuksel, Ulas; Kilikcier, Caglar; Olut, Sahin; Akar, Gözde; Ünal, Gözde; DİCLE, OĞUZ; SELVER, MUSTAFA ALPER (AVES Publishing Co., 2020-01-01) PURPOSE

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