Ümit Budak

2.2k citations

42 papers · 1.6k indexed · h-index 21

Impact in

Computer Vision and Pattern Recognition top 2%
- Digital Imaging for Blood Diseases
- Advanced Neural Network Applications
Radiology, Nuclear Medicine and Imaging top 2%
- Radiomics and Machine Learning in Medical Imaging
- Retinal Imaging and Analysis
- COVID-19 diagnosis using AI

Papers in

Computer Vision and Pattern Recognition 22
- Digital Imaging for Blood Diseases 8
- Image Retrieval and Classification Techniques 4
- Face and Expression Recognition 3
Ophthalmology 9
- Glaucoma and retinal disorders 7

Co-authors: Abdulkadir Şengür Yanhui Guo Zafer Cömert Deniz Korkmaz Hakan Açıkgöz Yaman Akbulut Varun Bajaj Musa Çıbuk
Journals: Health Information Science and Systems (3 papers)Measurement (2 papers)Journal of Digital Imaging (1 paper)Oral Surgery Oral Medicine Oral Pathology and Oral Radiology (1 paper)IEEE Geoscience and Remote Sensing Letters (1 paper)
Partner nations: Türkiye United States India

In The Last Decade

Ümit Budak

40 papers receiving 1.5k citations

Peers

Replace Naoufel Werghi with:

Naoufel Werghi United Arab Emirates

Shuihua Wang United Kingdom

Beiji Zou China

Anjan Gudigar India

Tehmina Khalil Pakistan

Syamsiah Mashohor Malaysia

Hong Song China

Junding Sun China

Khosro Rezaee Iran

Celia Shahnaz Bangladesh

Ümit Budak relative to Naoufel Werghi United Arab Emirates Naoufel Werghi's profile →

Citations per field

00.5×1.5×1.9×

Naoufel Werghi · 1×

×0.4 517/1k

CVPR

×1.0 542/517

RNMI

×1.9 158/82

NEURO

×0.9 602/671

AI

×1.3 149/116

OPHTH

Citations per year

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Countries citing papers authored by Ümit Budak

Since Specialization

Citations

This map shows the geographic impact of Ümit Budak's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ümit Budak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ümit Budak more than expected).

Fields of papers citing papers by Ümit Budak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ümit Budak. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ümit Budak. The network helps show where Ümit Budak may publish in the future.

Co-authors

The 25 scholars most cited alongside Ümit Budak, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ümit Budak Line = papers co-authored together Ümit Budak links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Maxillary sinus detection on cone beam computed tomography images using ResNet and Swin Transformer-based UNet Oral Surgery Oral Medicine Oral Pathology and Oral Radiology ·L.Z. Sun, Alicia Greenwood, Hüseyin Üzen, Ümit Budak, Muammer Türkoğlu, Davut Hanbay, Abdulkadir Şengür	2023	14
2	Photovoltaic cell defect classification based on integration of residual-inception network and spatial pyramid pooling in electroluminescence images Expert Systems with Applications ·Hakan Açıkgöz, Deniz Korkmaz, Ümit Budak	2023	29
3	Saldırı Tespiti için Makine Öğrenme Yöntemlerinin Karşılaştırmalı Analizi Bitlis Eren Üniversitesi Fen Bilimleri Dergisi ·Al Afgani Fadil, Musa Çıbuk, Ümit Budak	2021	3
4	Efficient COVID-19 Segmentation from CT Slices Exploiting Semantic Segmentation with Integrated Attention Mechanism Journal of Digital Imaging ·Ümit Budak, Musa Çıbuk, Zafer Cömert, Abdulkadir Şengür	2021	27
5	An improved residual-based convolutional neural network for very short-term wind power forecasting Energy Conversion and Management ·Ceyhun Yıldız, Hakan Açıkgöz, Deniz Korkmaz, Ümit Budak	2020	190
6	Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images Applied Soft Computing ·Ümit Budak, Zafer Cömert, Zryan Najat Rashid, Abdulkadir Şengür, Musa Çıbuk	2019	125
7	Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models Health Information Science and Systems ·Zafer Cömert, Abdulkadir Şengür, Ümit Budak, Adnan Fatıh Kocamaz	2019	49
8	An Effective Hybrid Model for EEG-Based Drowsiness Detection IEEE Sensors Journal ·Ümit Budak, Varun Bajaj, Yaman Akbulut, Orhan Atıla, Abdulkadir Şengür	2019	117
9	SegNet Mimarisi ile Bilgisayarlı Tomografi Görüntülerinden Karaciğer Bölgesinin Bölütlenmesi DergiPark (Istanbul University) ·Ümit Budak	2019	0
10	Efficient deep features selections and classification for flower species recognition Measurement ·Musa Çıbuk, Ümit Budak, Yanhui Guo, M. Cevdet İnce, Abdulkadir Şengür	2019	89
11	Cascaded deep convolutional encoder-decoder neural networks for efficient liver tumor segmentation Medical Hypotheses ·Ümit Budak, Yanhui Guo, Erkan Tanyıldızı, Abdulkadir Şengür	2019	108
12	DCCMED-Net: Densely connected and concatenated multi Encoder-Decoder CNNs for retinal vessel extraction from fundus images Medical Hypotheses ·Ümit Budak, Zafer Cömert, Musa Çıbuk, Abdulkadir Şengür	2019	50
13	Chronic Tympanic Membrane Diagnosis based on Deep Convolutional Neural Network Erdal Başaran, Zafer Cömert, Abdulkadir Şengür, Ümit Budak, Yüksel Çelik, Mesut Toğaçar	2019	34
14	A retinal vessel detection approach using convolution neural network with reinforcement sample learning strategy Measurement ·Titi Syartini, Ümit Budak, 信一郎田中, Elham S. Khorasani, Abdulkadir Şengür	2018	62
15	A novel retinal vessel detection approach based on multiple deep convolution neural networks Computer Methods and Programs in Biomedicine ·Yanhui Guo, Ümit Budak, Abdulkadir Şengür	2018	51
16	Transfer learning based histopathologic image classification for breast cancer detection Health Information Science and Systems ·Erkan Denız, Abdulkadir Şengür, Liu Lin, Yanhui Guo, Varun Bajaj, Ümit Budak	2018	249
17	Neutrosophic Hough Transform Axioms ·Ümit Budak, Yanhui Guo, Abdulkadir Şengür, Florentín Smarandache	2017	2
18	A Retinal Vessel Detection Approach Based on Shearlet Transform and Indeterminacy Filtering on Fundus Images Symmetry ·Yanhui Guo, Ümit Budak, Abdulkadir Şengür, Florentín Smarandache	2017	26
19	A novel approach based on image processing algorithms for microaneurysm candidate detection Ümit Budak, Abdulkadir Şengür, Yanhui Guo, Yaman Akbulut, 信一郎田中	2017	1
20	A novel microaneurysms detection approach based on convolutional neural networks with reinforcement sample learning algorithm Health Information Science and Systems ·Ümit Budak, Abdulkadir Şengür, Yanhui Guo, Yaman Akbulut	2017	43

About Ümit Budak

Ümit Budak is a scholar working on Computer Vision and Pattern Recognition, Ophthalmology, Health Informatics, Radiology, Nuclear Medicine and Imaging and Otorhinolaryngology, having authored 42 papers that have together received 1.6k indexed citations. Recurring topics across this work include Retinal Imaging and Analysis (10 papers), Digital Imaging for Blood Diseases (8 papers), Glaucoma and retinal disorders (7 papers), AI in cancer detection (7 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Image Retrieval and Classification Techniques (4 papers), Non-Invasive Vital Sign Monitoring (4 papers) and Face and Expression Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (517 citations), Radiology, Nuclear Medicine and Imaging (542 citations), Neurology (158 citations), Artificial Intelligence (602 citations) and Ophthalmology (149 citations). Ümit Budak has collaborated with scholars based in Türkiye, United States and India. Frequent co-authors include Abdulkadir Şengür, Yanhui Guo, Zafer Cömert, Deniz Korkmaz, Hakan Açıkgöz, Yaman Akbulut, Varun Bajaj, Musa Çıbuk, Ceyhun Yıldız and Erkan Denız. Their work appears in journals such as Health Information Science and Systems, Measurement, Journal of Digital Imaging, Oral Surgery Oral Medicine Oral Pathology and Oral Radiology and IEEE Geoscience and Remote Sensing Letters.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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