Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi最新文献

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Tek görüntü üretimi için öz-dikkat modüllü koşulsuz üretken bir model 带自我关注模块的无条件生成模型，用于生成单幅图像

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Pub Date : 2023-11-15 DOI: 10.28948/ngumuh.1367602

Eyyüp Yildiz, Erkan Yüksel, Selcuk Sevgen

{"title":"Tek görüntü üretimi için öz-dikkat modüllü koşulsuz üretken bir model","authors":"Eyyüp Yildiz, Erkan Yüksel, Selcuk Sevgen","doi":"10.28948/ngumuh.1367602","DOIUrl":"https://doi.org/10.28948/ngumuh.1367602","url":null,"abstract":"Generative models have recently become a prominent research topic in the field of artificial intelligence. Among these models, Generative Adversarial Networks (GAN) have revolutionized the field of deep learning by enabling the production of high-quality synthetic data that is very similar to real-world data. However, the effectiveness of GANs largely depends on the size and quality of training data. In many real-world applications, collecting large amounts of high-quality training data is impractical, time-consuming, and expensive. Accordingly, in recent years, there has been intense interest in the development of GAN models that can work with limited data. These models are particularly useful in scenarios where available data is sparse, such as medical imaging, or in creative applications such as creating new works of art. In this study, we propose a GAN model that can learn from a single training image. Our model is based on the principle of multiple GANs operating sequentially at different scales. At each scale, the GAN learns the features of the training image in different dimensions and transfers them to the next GAN. Samples produced by the GAN at the finest scale are images that have the characteristics of the training image but have different realistic structures. In our model, we utilized a self-attention module to increase the realism and quality of the generated images. Additionally, we used a new scaling method to increase the success of the model. The quantitative and qualitative results we obtained from our experimental studies show that our model performs image generation successfully. In addition, we demonstrated the robustness of our model by testing its success in different image manipulation applications. As a result, our model can successfully produce realistic, high-quality, diverse images from a single training image, providing short training time, memory efficiency, and good training stability. Our model is flexible enough to be used in areas where limited data needs to be worked on.","PeriodicalId":508079,"journal":{"name":"Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi","volume":"13 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139272091","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Farklı oranlardaki bazalt fiber takviyesinin kaolinin serbest basınç dayanımına etkisi 不同比例的玄武岩纤维加固对高岭土自由抗压强度的影响

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Pub Date : 2023-11-13 DOI: 10.28948/ngumuh.1352665

Yasemin ASLAN TOPÇUOĞLU, Zülfü Gürocak

{"title":"Farklı oranlardaki bazalt fiber takviyesinin kaolinin serbest basınç dayanımına etkisi","authors":"Yasemin ASLAN TOPÇUOĞLU, Zülfü Gürocak","doi":"10.28948/ngumuh.1352665","DOIUrl":"https://doi.org/10.28948/ngumuh.1352665","url":null,"abstract":"There are many materials used to stabilize or reinforcement low strength soils. While additives such as fly ash, lime, tuff, silica fume are preferred in stabilization works, fibers are used in reinforcement works. The use of fiber, which has emerged as an alternative to traditional methods, has become widespread. The most preferred fiber types in soil reinforcement are glass, polypropylene and basalt fibers. Basalt fiber, which is produced from basalt rock and widely distributed in nature, was chosen as a reinforcement material in this study, which is increasingly used due to its high strength, economic, environmentally friendly, natural and many other superior properties. The aim of this study is to examine the effects of basalt fiber ratio on strength in low plasticity kaolin clay reinforced with basalt fiber. For this purpose, unconfined pressure tests were carried out on cylindrical samples prepared by adding 6 mm long basalt fiber at different rates to clay and compressing it at optimum water content. In the samples reinforced with basalt fiber, the maximum strength was obtained in the sample with 2% basalt fiber ratio. It was determined that the strength decreased in samples with higher basalt fiber content.","PeriodicalId":508079,"journal":{"name":"Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139279157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flotation of low-rank coal slimes 低级煤泥的浮选

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi Pub Date : 2023-11-09 DOI: 10.28948/ngumuh.1324175

V. Önen, Mustafa Kutkan Karaoğlan

引用次数: 0

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