Replication study: Development and validation of deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs [PDF]
, 2018 Replication studies are essential for validation of new methods, and are crucial to maintain the high standards of scientific publications, and to use the results in practice.
Bongo, Lars Ailo +2 more
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Waste material classification using performance evaluation of deep learning models
Journal of Intelligent Systems, 2023 Waste classification is the issue of sorting rubbish into valuable categories for efficient waste management. Problems arise from issues such as individual ignorance or inactivity and more overt issues like pollution in the environment, lack of resources,
Al-Mashhadani Israa Badr
doaj +1 more source
ENHANCING DISEASE DETECTION PREDICTION ACCURACY OF GRAPE LEAVES USING VGG16 MODEL AND INCEPTION V3 MODEL [PDF]
Proceedings on Engineering SciencesPlant diseases can impact the leaves at any point from sowing to harvesting, resulting in significant losses in crop production and market economic value.
Deepshikha Yadav +3 more
doaj +1 more source
, 2020 Navigation and mobility are some of the major problems faced by visually impaired people in their daily lives. Advances in computer vision led to the proposal of some navigation systems. However, most of them require expensive and/or heavy hardware.
Breve, Fabricio +1 more
core +1 more source
Bone Fracture Detection through Advanced Neural Network Architectures [PDF]
E3S Web of ConferencesDetecting bone fractures accurately is essential in radiology, as missed diagnoses can seriously affect patient health. This study introduces a deep learning approach using the InceptionV3 model, designed to identify fractures in high-resolution CT ...
Venkatesam Anne Sreyas +5 more
doaj +1 more source
Revolutionizing Automotive Parts Classification Using InceptionV3 Transfer Learning
International Journal Software Engineering and Computer Science (IJSECS), 2023 This study presents a novel methodology for classifying automotive parts by implementing the Transfer Learning technique, utilizing the InceptionV3 architecture. We use a proprietary dataset encompassing diverse categories of automotive components for training and evaluating the model.
openaire +1 more source
Skin Disease Detection Using VGG16 and InceptionV3
International Journal of Intelligent Systems and Applications in Engineering, 2023 Accurate diagnosis and timely treatment of skin diseases present formidable challenges, posing potential health risks to individuals affected. This research paper delves into an extensive exploration of skin disease detection employing two renowned deep learning architectures: VGG16 and InceptionV3.
Sayyad, Jilani +2 more
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Towards Analyzing Semantic Robustness of Deep Neural Networks
, 2019 Despite the impressive performance of Deep Neural Networks (DNNs) on various vision tasks, they still exhibit erroneous high sensitivity toward semantic primitives (e.g. object pose). We propose a theoretically grounded analysis for DNN robustness in the
A Fawzi +7 more
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Comparative evaluation of lightweight and pre-trained deep learning models for multi-class classification of infected freshwater fish species in Thailand [PDF]
Veterinary WorldBackground and Aim: Aquaculture plays a crucial role in global food security; however, disease outbreaks remain a major constraint to sustainable production. Rapid and reliable detection of fish diseases is essential to reduce mortality, economic losses,
Sivaramasamy Elayaraja +3 more
doaj +1 more source
Food Image Classification Based on CBAM-Inception V3 Transfer Learning
Liang you shipin ke-jiTo improve the accuracy of automatic recognition and classification of food images, a classification model CBAM- InceptionV3 is proposed, which embeds the Convolutional Block Attention Module.
DU Hui-jiang +3 more
doaj +1 more source