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Deep learning for inverse problems in imaging
(IEEE, 2019)
Inverse problems have been widely studied in image processing, with applications in areas such as image denoising, blind/non-blind deblurring, super-resolution and compressive sensing. Lately deep learning techniques and ...
Uzaktan algılanan görüntülerde bina yoğunluğu kestirimi için derin öğrenme
(Institute of Electrical and Electronics Engineers Inc., 2019)
Bu bildiri, derin öğrenme yöntemleri uygulayarak uzaktan algılamalı optik görüntülerde bina yoğunluğunun noktasal olarak kestirilmesi ile ilgilidir. Bu çalışma kapsamında, evrişimsel sinir ağına (ESA) dayalı derin öğrenme ...
Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM
(Institute of Electrical and Electronics Engineers Inc., 2020)
The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on ...
Geniş alan görüntülerinde anomali tespiti
(Institute of Electrical and Electronics Engineers Inc., 2021)
Bu çalışma hava araçlarından çekilmiş geniş alan görüntülerindeki anomalileri tespit etmek ile ilgilidir. Anomali kümesi normal seyrin dışındaki her şey olarak belirlenmiştir. Bu amaçla iki farklı veri seti kullanılmış ve ...
Improved YOLOv4 for aerial object detection
(Institute of Electrical and Electronics Engineers Inc., 2021)
Drones equipped with cameras are being used for surveillance purposes. These surveillance systems need vision-based object detection of ground objects which look very small because of the altitude of drones. We propose an ...
Small object detection and tracking from aerial imagery
(Institute of Electrical and Electronics Engineers Inc., 2021)
Object detection and tracking from airborne imagery draws attention to the parallel development of UAV systems and computer vision technologies. Aerial imagery has its own unique challenges that differ from the training ...
Deep learning-based blind image super-resolution using iterative networks
(Institute of Electrical and Electronics Engineers Inc., 2021)
Deep learning-based single image super-resolution (SR) consistently shows superior performance compared to the traditional SR methods. However, most of these methods assume that the blur kernel used to generate the ...
Iterative kernel reconstruction for deep learning-based blind image super-resolution
(IEEE Computer Society, 2022)
Deep learning based methods have received a great deal of interest in recent years to solve the single image superresolution (SISR) problem and their performance is proven to be superior when compared to classical SR ...