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Toplam kayıt 16, listelenen: 11-16
Deep Learning Based Focus Measurement Operator for 3D Imaging in Microscopic Systems
(IEEE, 2023)
Since 3D imaging in microscopic systems makes cell and tissue structures more prominent and visible, it provides higher performance in image processing applications such as automatic segmentation, recognition, classification, ...
An Efficient 1D Autoencoder-Based Approach for R-Peaks Detection in Electrocardiogram Signals
(Institute of Electrical and Electronics Engineers Inc., 2023)
Electrocardiogram (ECG) signal which is composition of multiple segments such as P-wave, QRS complex and T-wave plays a crucial role in evaluating human heart cardiac diagnosis. For an analysis of cardiac diagnosis, it is ...
A Hybrid CNN-LSTM Framework for Unsupervised Anomaly Detection in Water Distribution Plant
(Institute of Electrical and Electronics Engineers Inc., 2023)
To reduce potential threats to public health and economic losses, water distribution systems, which are critical parts of industrial control systems, require accurate and effective anomaly detection. The successful ...
Detection of pneumonia from pediatric chest X-ray images by transfer learning
(YILDIZ TECHNICAL UNIV, 2024)
When pathogens such as viruses, bacteria and fungi attack the lungs, the alveoli fill with inflamed fluid, causing pneumonia. Early diagnosis of this disease, which has fatal outcomes especially in children under 5 years ...
An Extensive Study: Creation of A New Inverted Microscope Image Data Set and Improving Auto-Encoder Models for Higher Accuracy Segmentation of HaCaT Cell Culture Line
(Institute of Electrical and Electronics Engineers Inc., 2023)
In cell culture investigations, it is assumed that the number of cells is counted automatically without the need for forward planning, additional tools, or consumables. The automatic cell counting process is greatly ...
DL-EDOF: Novel Multi-Focus Image Data Set and Deep Learning-Based Approach for More Accurate and Specimen-Free Extended Depth of Focus
(Springer Nature, 25.03.2024)
Depth of focus (DOF) is defined as the axial range in which the specimen stage moves without losing focus while the imaging apparatus remains stable. It may not be possible to capture an image that includes the entire ...