Nuh Alpaslan

521 total citations
29 papers, 383 citations indexed

About

Nuh Alpaslan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Oncology. According to data from OpenAlex, Nuh Alpaslan has authored 29 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 6 papers in Oncology. Recurrent topics in Nuh Alpaslan's work include Image Retrieval and Classification Techniques (7 papers), AI in cancer detection (6 papers) and Medical Image Segmentation Techniques (5 papers). Nuh Alpaslan is often cited by papers focused on Image Retrieval and Classification Techniques (7 papers), AI in cancer detection (6 papers) and Medical Image Segmentation Techniques (5 papers). Nuh Alpaslan collaborates with scholars based in Türkiye and United States. Nuh Alpaslan's co-authors include Ahu Dikilitaş, Alihan Bozoğlan, Hacer Sahin, Kazım Hanbay, Abdullah Seçkin Ertuğrul, Davut Hanbay, Muhammed Fatih Talu, Hüseyin Fırat, Prabir Bhattacharya and Mahmudur Rahman and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Nuh Alpaslan

28 papers receiving 373 citations

Peers

Countries citing papers authored by Nuh Alpaslan

Since Specialization

Citations

This map shows the geographic impact of Nuh Alpaslan'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 Nuh Alpaslan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nuh Alpaslan more than expected).

Fields of papers citing papers by Nuh Alpaslan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nuh Alpaslan. 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 Nuh Alpaslan. The network helps show where Nuh Alpaslan may publish in the future.

Co-authorship network of co-authors of Nuh Alpaslan

This figure shows the co-authorship network connecting the top 25 collaborators of Nuh Alpaslan. A scholar is included among the top collaborators of Nuh Alpaslan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nuh Alpaslan. Nuh Alpaslan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	Evrişimsel Sinir Ağı Mimarileri ve Öğrenim Aktarma ile Bitki Zararlısı Çekirge Türlerinin Sınıflandırması	Fırat Üniversitesi Mühendislik Bilimleri Dergisi	Nuh Alpaslan, Davut Hanbay et al.	3
2	Wind Speed Prediction Using Meteorological Measurements for Elazığ Province	DergiPark (Istanbul University)	Nuh Alpaslan et al.	0
3	Neutrosophic set based local binary pattern for texture classification	Expert Systems with Applications	Nuh Alpaslan	9
4	Robust optimization of SegNet hyperparameters for skin lesion segmentation	Multimedia Tools and Applications	Nuh Alpaslan, Davut Hanbay et al.	19
5	Robust optimization of SVM hyper-parameters for spillway type selection	Ain Shams Engineering Journal	Nuh Alpaslan, M. Emin Emiroğlu et al.	18
6	A Novel Texture Classification Method Based on Neutrosophic Truth	SHILAP Revista de lepidopterología	Nuh Alpaslan	1
7	An effective approach to the two-dimensional rectangular packing problem in the manufacturing industry	Computers & Industrial Engineering	Hüseyin Fırat, Nuh Alpaslan	19
8	Cilt Lezyon Bölütlemesi için Metasezgisel Temelli Otsu Eşikleme Yöntemi	Türk doğa ve fen dergisi :	Nuh Alpaslan et al.	1
9	Multi-Scale Shape Index-Based Local Binary Patterns for Texture Classification	IEEE Signal Processing Letters	Nuh Alpaslan, Kazım Hanbay	16
10	SegNet Mimarisi Kullanılarak Cilt Lezyon Bölütleme Performansının İyileştirilmesi	European Journal of Science and Technology	Nuh Alpaslan et al.	5
11	Multi-Resolution Intrinsic Texture Geometry-Based Local Binary Pattern for Texture Classification	IEEE Access	Nuh Alpaslan, Kazım Hanbay	29
12	Sezgisel Algoritmalar Kullanılarak İki Boyutlu Dikdörtgen Şerit Paketleme Probleminin Çözümü	European Journal of Science and Technology	Hüseyin Fırat, Nuh Alpaslan	1
13	MEME KANSERİ TANISI İÇİN DERİN ÖZNİTELİK TABANLI KARAR DESTEK SİSTEMİ		Nuh Alpaslan	3
14	Automated melanoma recognition in dermoscopic images based on extreme learning machine (ELM)	Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE	Md Mahmudur Rahman, Nuh Alpaslan	3
15	Developing a retrieval based diagnostic aid for automated melanoma recognition of dermoscopic images		Mahmudur Rahman, Nuh Alpaslan et al.	21
16	Calculation of melatonin and resveratrol effects on steatosis hepatis using soft computing methods	Computer Methods and Programs in Biomedicine	Muhammed Fatih Talu, Mehmet Gül et al.	6
17	Comparison of peri‐implant crevicular fluid levels of adrenomedullin and human beta defensins 1 and 2 from mandibular implants with different implant stability quotient levels in nonsmoker patients	Journal of Periodontal Research	Abdullah Seçkin Ertuğrul, Nuh Alpaslan et al.	7
18	Calculation of drug effectiveness on treatment of steatosis hepatis using HOG based ANN.	DergiPark (Istanbul University)	Nuh Alpaslan et al.	2
19	Comparison of CCL28, interleukin‐8, interleukin‐1β and tumor necrosis factor‐alpha in subjects with gingivitis, chronic periodontitis and generalized aggressive periodontitis	Journal of Periodontal Research	Abdullah Seçkin Ertuğrul, Hacer Sahin et al.	102
20	Gingival crevicular fluid adrenomedullin level in individuals with and without diabetes mellitus type 2	Journal of Periodontal Research	Abdullah Seçkin Ertuğrul, Ahu Dikilitaş et al.	6

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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