A Simple Methodology for 2D Reconstruction Using a CNN Model
Sign Up to like & getrecommendations! Published in 2020 at "Pattern Recognition"
DOI: 10.1007/978-3-030-49076-8_10
Abstract: In recent years, Deep Learning research have demonstrated their effectiveness in digital image processing, mainly in areas with heavy computational load. Such is the case of aerial photogrammetry, where the principal objective is to generate… read more here.
Keywords: methodology reconstruction; methodology; cnn model; reconstruction using ... See more keywords
A loss combination based deep model for person re-identification
Sign Up to like & getrecommendations! Published in 2017 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-017-5009-y
Abstract: The Convolutional Neural Network (CNN) has significantly improved the state-of-the-art in person re-identification (re-ID). In the existing available identification CNN model, the softmax loss function is employed as the supervision signal to train the CNN… read more here.
Keywords: cnn model; person; deep features; cnn ... See more keywords
A 3 Tier CNN model with deep discriminative feature extraction for discovering malignant growth in multi-scale histopathology images
Sign Up to like & getrecommendations! Published in 2021 at "Informatics in Medicine Unlocked"
DOI: 10.1016/j.imu.2021.100616
Abstract: Abstract The Convolutional Neural Network (CNN) is intended to generalize and automatically learn spatial hierarchies of features, using stacked convolution-pooling layers with Backpropagation of errors. Two predominant challenges confronted while applying the CNN model for… read more here.
Keywords: cnn model; tier cnn; model; histopathology ... See more keywords
Identifying Triage Determinants and Using a Novel Bayesian 3D-CNN Model for COVID-19 Mass Casualty Incidents (MCI) Triage Recommendation
Sign Up to like & getrecommendations! Published in 2024 at "Disaster Medicine and Public Health Preparedness"
DOI: 10.1017/dmp.2024.224
Abstract: Abstract Objective This research identified the key determinants and designed a novel Bayesian three-dimension convolution neural network (3D-CNN) for COVID-19 mass casualty incidents (MCI) triage recommendation. Methods 109 articles between 2019 and 2022 were archived… read more here.
Keywords: triage; triage recommendation; cnn model;
Scalar invariant transform based deep learning framework for detecting heart failures using ECG signals
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-53107-y
Abstract: Heart diseases are leading to death across the globe. Exact detection and treatment for heart disease in its early stages could potentially save lives. Electrocardiogram (ECG) is one of the tests that take measures of… read more here.
Keywords: cnn model; heart; ecg signals; model ... See more keywords
Evaluation of CNN model by comparing with convolutional autoencoder and deep neural network for crop classification on hyperspectral imagery
Sign Up to like & getrecommendations! Published in 2020 at "Geocarto International"
DOI: 10.1080/10106049.2020.1740950
Abstract: Identification of crops is an important topic in the agricultural domain. Hyperspectral remote sensing data are very useful for crop feature extraction and classification. Remote sensing data is an... read more here.
Keywords: comparing convolutional; classification; crop; cnn model ... See more keywords
Artificial intelligence predicts all-cause and cardiovascular mortalities using 12-lead electrocardiography in sinus rhythm
Sign Up to like & getrecommendations! Published in 2023 at "Europace"
DOI: 10.1093/europace/euad122.291
Abstract: Abstract Funding Acknowledgements Type of funding sources: None. Introduction Electrocardiography (ECG) can be easily obtained at a low cost and includes voltage and time interval representing heart conditions. We hypothesized that artificial intelligence (AI) detects… read more here.
Keywords: electrocardiography; cnn model; cause death; death ... See more keywords
A Deep Convolutional Neural Network Using MRI: Automated Differentiation between Osteoporotic Vertebral Fracture and Vertebral Compression Fractures Due to Spinal Metastasis.
Sign Up to like & getrecommendations! Published in 2021 at "Spine"
DOI: 10.1097/brs.0000000000004307
Abstract: STUDY DESIGN Retrospective study of magnetic resonance imaging (MRI). OBJECTIVES To assess the ability of a convolutional neural network (CNN) model to differentiate osteoporotic vertebral fractures (OVFs) and malignant vertebral compression fractures (MVFs) using short-TI… read more here.
Keywords: spine surgeons; neural network; cnn model; accuracy ... See more keywords
A Deep Learning Framework for Cycling Maneuvers Classification
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2898852
Abstract: In recent years, cycling has become increasingly popular globally, which takes up little space and leads to nearly no environmental damage. Bicycles permit daily commuters to travel in an efficient manner through frequent traffic congestion.… read more here.
Keywords: cnn model; cycling maneuvers; model; classification ... See more keywords
A Dilated CNN Model for Image Classification
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DOI: 10.1109/access.2019.2927169
Abstract: The dilated convolution algorithm, which is widely used for image segmentation, is applied in the image classification field in this paper. In many traditional image classification algorithms, convolution neural network (CNN) plays an important role.… read more here.
Keywords: model; image classification; cnn model; dilated cnn ... See more keywords
A New Deep CNN Model for Environmental Sound Classification
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.2984903
Abstract: Cognitive prediction in the complicated and active environments is of great importance role in artificial learning. Classification accuracy of sound events has a robust relation with the feature extraction. In this paper, deep features are… read more here.
Keywords: environmental sound; classification; cnn model; sound classification ... See more keywords