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QuickQual: Lightweight, Convenient Retinal Image Quality Scoring with Off-the-Shelf Pretrained Models
Image quality remains a key problem for both traditional and deep learning (DL)-based approaches to retinal image analysis and identifying poor...
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Automated Method for Optimum Scale Search when Using Trained Models for Histological Image Analysis
AbstractPreparation of input data for an artificial neural network is a key step to achieve a high accuracy of its predictions. It is well known that...
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Ensemble-based advancements in maternal fetal plane and brain plane classification for enhanced prenatal diagnosis
In the realm of maternal healthcare, accurate fetal plane detection is of paramount importance. This paper introduces a novel approach that leverages...
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A comprehensive exploration of deep learning approaches for pulmonary nodule classification and segmentation in chest CT images
Accurately determining whether nodules on CT images of the lung are benign or malignant plays an important role in the early diagnosis and treatment...
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A comparison of methods for image classification of cultural heritage using transfer learning for feature extraction
Image recognition and classification in the domain of cultural heritage is a complex task that usually requires good image quality and a large...
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Semantic road segmentation using encoder-decoder architectures
Road detection is a fundamental task in autonomous driving, making accurate and efficient road area segmentation essential for the safe and precise...
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Impact of image enhancement methods on lung disease diagnosis using x-ray images
Nowadays, Lung disease is the most common and fatal disease around the world. It causes patients to experience shortening of breath, fever, and...
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An early-stage diagnosis of diabetic retinopathy based on ensemble framework
Diabetic retinopathy (DR) is one of the most common causes of vision loss worldwide. Early identification and detection of DR, aided by a retinal...
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Revisiting activation functions: empirical evaluation for image understanding and classification
In this paper, the authors have devised four novel activation functions by coupling and combining a few existing functions implemented with four...
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A Predictive Deep Learning Ensemble-Based Approach for Advanced Cancer Classification
Breast cancer is a significant contributor to the death rate of women in develo** and underdeveloped nations. Timely identification and...
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Weighted voting ensemble of hybrid CNN-LSTM Models for vision-based human activity recognition
This research work aims to propose an ensemble model of different pre-trained CNN networks combined with LSTM to detect a set of routine human...
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Diabetic Retinopathy Detection Using Novel Loss Function in Deep Learning
Globally, the number of diabetics has significantly increased in recent years. Several age groups are affected. Diabetic Retinopathy (DR) affects...
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A comparative study of grape crop disease classification using various transfer learning techniques
Grapes are one of the fruits, which provides a significant source of Vitamin C. Like the other plant diseases, grapes plants are also affected some...
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Transfer Learning for COVID-19 Detection in Medical Images
As of late, the COVID infection 2019 (COVID-19) has caused a pandemic sickness in more than 200 nations, therefore impacting billions of people. To...
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Implementation Challenges and Strategies for Hebbian Learning in Convolutional Neural Networks
AbstractGiven the unprecedented growth of deep learning applications, training acceleration is becoming a subject of strong academic interest....
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Fingerprint pattern classification using deep transfer learning and data augmentation
Decreasing the number of matching comparisons between presented fingerprints and their respective templates in automated fingerprint identification...
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An improved residual learning model and its application to hardware image classification
Some hardware is similar in color and shape between different classes, and some hardware varies within a class, thereby decreasing the accuracy of...
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Supremacy of attention-based transformer in oral cancer classification using histopathology images
Oral cancer has emerged as one of the ubiquitous malignant tumors globally. Timely detection and treatment reduces the mortality rate of oral cancer....
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Optimal Layer Selection on Deep Convolutional Neural Networks Using Backward Freezing and Binary Search
Transfer Learning in Deep Convolutional Neural Networks is a highly used method for image classification, the performance depends on the selection of...
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PETLFC: Parallel ensemble transfer learning based framework for COVID-19 differentiation and prediction using deep convolutional neural network models
Despite a worldwide research involvement in the global COVID-19 pandemic, the research community is still struggling to develop reliable and faster...
