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Transformer-Based Contrastive Learning Method for Automated Sleep Stages Classification
Automated sleep stages classification facilitates clinical experts in conducting treatment for sleep disorders, as it is more time-efficient...
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Towards an Automated Classification of Software Libraries
Nowadays, the use of third-party libraries in software is common. At the same time, the number of published libraries continues to increase. An...
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Automated micro aneurysm classification using deep convolutional spike neural networks
One of the common diseases in people with micro aneurysms is diabetic retinopathy (DR). Due to a lack of early diagnosis, diabetic retinopathy poses...
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Automated Seed Classification Using State-of-the-Art Techniques
The demand for efficient and accurate seed assessment is paramount in modern agriculture to ensure good crop yield. This work presents a system for...
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Clustered Automated Machine Learning (CAML) model for clinical coding multi-label classification
Clinical coding is a time-consuming task that involves manually identifying and classifying patients’ diseases. This task becomes even more...
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A fully automated classification of third molar development stages using deep learning
Accurate classification of tooth development stages from orthopantomograms (OPG) is crucial for dental diagnosis, treatment planning, age assessment,...
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Deer Hunting Optimization with Deep Learning-Driven Automated Fabric Defect Detection and Classification
The detection of fabric defects (FD) has become crucial in the fabric industry; however, it has some limitations due to the complex shapes and...
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Automated hyperparameter tuning for crack image classification with deep learning
Deep learning methods have relevant applications in crack detection in buildings. However, one of the challenges in this field is the hyperparameter...
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Automated classification of big X-ray diffraction data using deep learning models
In current in situ X-ray diffraction (XRD) techniques, data generation surpasses human analytical capabilities, potentially leading to the loss of...
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Improving Image Classification of Knee Radiographs: An Automated Image Labeling Approach
Large numbers of radiographic images are available in musculoskeletal radiology practices which could be used for training of deep learning models...
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ConcatNeXt: An automated blood cell classification with a new deep convolutional neural network
Examining peripheral blood smears is valuable in clinical settings, yet manual identification of blood cells proves time-consuming. To address this,...
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Deep Learning for Automated Classification of Hip Hardware on Radiographs
Purpose: To develop a deep learning model for automated classification of orthopedic hardware on pelvic and hip radiographs, which can be clinically...
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Automated classification of liver fibrosis stages using ultrasound imaging
BackgroundUltrasound imaging is the most frequently performed for the patients with chronic hepatitis or liver cirrhosis. However, ultrasound imaging...
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Selection of pre-trained weights for transfer learning in automated cytomegalovirus retinitis classification
Cytomegalovirus retinitis (CMVR) is a significant cause of vision loss. Regular screening is crucial but challenging in resource-limited settings. A...
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A survey on computer vision approaches for automated classification of skin diseases
Skin diseases are a significant concern for public health, demanding accurate diagnosis for effective treatment. However, traditional diagnostic...
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Auditory feedback in tele-rehabilitation based on automated gait classification
In this paper, we describe a proof-of-concept for the implementation of a wearable auditory biofeedback system based on a sensor-instrumented insole....
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Prostate classification network (PC-Net) for automated classification of Prostate cancer in Magnetic resonance imaging
Prostate cancer (PCa) is found to be the second most common cause of death in men after lung cancer, making it necessary to diagnose as early as...
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Automated retinal disease classification using hybrid transformer model (SViT) using optical coherence tomography images
Optical coherence tomography (OCT) is a widely used imaging technique in ophthalmology for diagnosis and treatment. Recent advances in deep neural...
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Automated Pest Detection Using Image Classification
The automated pest detection project is a web application designed to assist farmers in identifying plant diseases and providing suitable solutions....
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An automated histological classification system for precision diagnostics of kidney allografts
For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has...
