WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Conference Object Covariance Features for Trajectory Analysis(Institute of Electrical and Electronics Engineers Inc., 2016) Karadeniz, T.; Maras, H.H.In this work, we aimed to demonstrate that covariance estimation methods can be used for trajectory classification. We have shown that, features obtained via shrunk covariance estimation are suitable for describing trajectories. We have arrived to the conclusion that, when compared to Dynamic Time Warping, the explained technique is faster and may yield more accurate results. © 2017 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 1Dengesiz Epilepsi Veri Seti İçin Sınıflandırmada Farklı SMOTE Yöntemlerinin Etkileri(Institute of Electrical and Electronics Engineers Inc., 2025) Calis, Ahmet Gokay; Ergezer, HalitIn this study, the effects of different SMOTE methods on machine learning algorithms for the imbalanced epilepsy dataset were investigated. After filtering, the imbalanced dataset was balanced with 5 different SMOTE methods and classified with various machine learning algorithms. Coarse-K-Nearest Neighbor, Bagged Trees, and Artificial Neural Networks models were evaluated in epilepsy detection. The performance of these different models was compared with Matthews Correlation Coefficient (MCC) and F1 Score metrics. The results showed that the Borderline-SMOTE algorithm had the highest F1 Score and MCC values among all machine learning algorithms. © 2025 Elsevier B.V., All rights reserved.Conference Object AviBERT: Transformer Tabanlı Hava Aracı Metni Sınıflandırma(Institute of Electrical and Electronics Engineers Inc., 2025) Unal, Muhammed Cihat; Yurtalan, Gokhan; Karatas, Yahya Bahadir; Karamanlioglu, Alper; Demirel, BerkanIn recent years, transformer-based models pre-trained on extensive corpora have played a critical role in the advancement of Natural Language Processing methodologies. Particularly, methods based on BERT have demonstrated remarkable performance across various tasks by offering robust capabilities in deeply understanding texts semantically. However, despite these advancements, there is a notable scarcity of studies applying these technologies in the aviation sector. This paper develops a multi-class classification model for aviation-specific texts using variants of BERT. The study encompasses the processes of collecting web content related to aircraft, labeling and model training. The details of the dataset are explained and the outcomes of the study are assessed based on the macro F1-score and accuracy of different models. © 2025 Elsevier B.V., All rights reserved.Conference Object Citation - WoS: 1Citation - Scopus: 1A Fast and Optimal Static Segment Scheduling Method for Flexray V3.0(Institute of Electrical and Electronics Engineers Inc., 2017) Cakmak, C.; Schmidt, E.G.; Schmidt, K.W.We propose a novel and fast frame scheduling method for the Static Segment (SS) of the new in-vehicle network standard FlexRay v3.0 in this paper. The proposed methods assigns frames to the SS using the minimum number of time slots based on an Integer Linear Programming formulation. Different from the existing method in the literature, the proposed method computes optimal frame schedules within miliseconds. © 2017 IEEE.Conference Object A Configurable Can Fd Controller: Architecture and Implementation(Institute of Electrical and Electronics Engineers Inc., 2017) Afsin, M.E.; Schmidt, K.W.; Schmidt, E.G.CAN FD is a new standard which provides fast data rate while preserving the compatibility with CAN (controller area network). In this paper, a Configurable IP core architecture (A-CAN) which is compatible with the CAN FD standard, is proposed. Different than existing CAN/CAN FD controllers, the numbers and sizes of transmit and receive buffers of A-CAN can be configured in run time. To this end, A-CAN enables the best use of single controller hardware for different applications and enables improving the real time communication performance. A-CAN communicates with the host device over SPI without any specific interface requirements. A-CAN is implemented on an FPGA Evaluation Board and its functionally is verified at a rate of 2 Mbps. © 2017 IEEE.Conference Object An Analysis on the Effect of Skip Connections in Fully Convolutional Networks for License Plate Localization(Institute of Electrical and Electronics Engineers Inc., 2019) Uzun, E.; Akagunduz, E.In this study, the effect of the skip connections, which are seen in fully convolutional networks, on object localization is analyzed. For this purpose, a local data set for plate detection is created. Experiments are carried out using this data set. Due to the small size of the image set, data augmentation method is used to overcome the danger of over-fitting. The learning rates of the first layers are frozen for analysis and finetuning is applied to only the last layer and deconvolution layers. The results obtained are compared with the results of other image sets. The results indicate the importance of the information provided by the skip connections on object localization. © 2019 IEEE.Conference Object Citation - WoS: 2Citation - Scopus: 2A Two Stage Template Matching Algorithm and Its Implementation on Fpga(Institute of Electrical and Electronics Engineers Inc., 2015) Sever, R.; Töreyin, B.U.; Aktaş, H.In this paper, to decrease the computational cost and number of cycles in Template Matching Algorithm, a novel two-stage algorithm is proposed. The Sum of Absolute Differences method is used for matching. The proposed algorithm is implemented on Field-Programmable-Gate-Array (FPGA). The algorithm is accelerated with the effective usage of Block RAMs distributed on FPGA. Thus, the proposed algorithm became fast enough for real time object tracking applications on UAVs. © 2015 IEEE.