Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Serum Creatinine Detection in a Microfluidic Chip Using a Smartphone Camera(Chemical and Biological Microsystems Society, 2022) Karakuzu, B.; Tarim, E.A.; Tekin, H.C.We present a microfluidic chip platform to detect serum creatinine levels using the enzyme-linked immunosorbent assay (ELISA) principle. In the platform, surface modified microfluidic channel sensitively captured target molecules from the serum sample, and then ELISA protocol was applied inside the channels. Afterward, the blue color formed as a result of the enzymatic reaction was measured via a smartphone camera. The proposed strategy allows the detection of creatinine rapidly in a minute amount of the serum samples without the need for expensive equipment. Thus, chronic kidney disease (CKD) could be monitored easily at point-of-care settings via the proposed creatinine detection strategy. © 2022 MicroTAS 2022 - 26th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.Article Citation - WoS: 43Citation - Scopus: 47Semantic Segmentation of Outdoor Panoramic Images(Springer, 2021) Orhan, Semih; Baştanlar, YalınOmnidirectional cameras are capable of providing 360. field-of-view in a single shot. This comprehensive view makes them preferable for many computer vision applications. An omnidirectional view is generally represented as a panoramic image with equirectangular projection, which suffers from distortions. Thus, standard camera approaches should be mathematically modified to be used effectively with panoramic images. In this work, we built a semantic segmentation CNN model that handles distortions in panoramic images using equirectangular convolutions. The proposed model, we call it UNet-equiconv, outperforms an equivalent CNN model with standard convolutions. To the best of our knowledge, ours is the first work on the semantic segmentation of real outdoor panoramic images. Experiment results reveal that using a distortion-aware CNN with equirectangular convolution increases the semantic segmentation performance (4% increase in mIoU). We also released a pixel-level annotated outdoor panoramic image dataset which can be used for various computer vision applications such as autonomous driving and visual localization. Source code of the project and the dataset were made available at the project page (https://github.com/semihorhan/semseg-outdoor-pano). © 2021, The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature.