darknet-19 (MathWorks Inc)

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MathWorks Inc darknet-19
Darknet 19, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/darknet-19/pmc11001234-84-17-1
Average 90 stars, based on 1 article reviews

darknet-19 - by Bioz Stars, 2026-11

90/100 stars

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Article Title: Deep learning-based CNN for multiclassification of ocular diseases using transfer learning
Article Snippet: The accuracy and loss function plot of the Darknet-53 (batch size-6, optimiser-SGDM) obtained during the training process in MATLAB 2023 is shown in Figures 14 and 15, respectively.

Article Title: In vivo identification of angle dysgenesis and its relation to genetic markers associated with glaucoma using artificial intelligence
Article Snippet: In MATLAB, all the available 19 pretrained convolutional neural network (CNN) models, including SqueezeNet, ResNet-18, GoogleNet, ResNet-50, DarkNet-53, DarkNet-19, ShuffleNet, NasnetMobile, Nasnet Large, Xception, Place-365-Google, MobileNet V2, DenseNet-201, Inception-ResNet V2, Inception-V3, ResNet-101, VGG-19, VGG-16, and AlexNet, were trained using our datasets.

Article Title: A deep learning-based radiomics approach to predict head and neck tumor regression for adaptive radiotherapy
Article Snippet: We used the deep learning toolbox of MATLAB and downloaded 16 CNNs, SqueezeNet, GoogleNet, Inceptionv3, DenseNet201, MobileNetv2, ResNet18, ResNet50, ResNet101, Xception, InceptionResNetv2, ShuffleNet, NASNetMobile, NASNetLarge, DarkNet19, DarkNet53, and AlexNet, all pretrained on the ImageNet Large-Scale Visual Recognition Challenge (ILSVRC) .

Article Title: Deep-learning model for diagnostic clue: detecting the dural tail sign for meningiomas on contrast-enhanced T1 weighted images
Article Snippet: We used the “Deep Learning Toolbox” in Matlab to train the YOLOv4 model, and a YOLO v4 network was initialized using the transfer learning method based on a pre-trained DarkNet53 ( ) with the following parameters: nine anchor boxes, Adam optimizer, mini-batch size of 4, initial learning rate of 1×10 −3 , factor for L2 regularization of 5×10 −4 , and 50 epochs at maximum.

Article Title: Topical Henna Application Causing Acute Kidney Injury and Acute Hemolytic Anemia.
Article Snippet: In MATLAB, all the available 19 pretrained convolutional neural network (CNN) models, including SqueezeNet, ResNet‐18, GoogleNet, ResNet‐50, DarkNet‐53, DarkNet‐19, ShuffleNet, NasnetMobile, Nasnet Large, Xception, Place‐365‐Google, MobileNet V2, DenseNet‐201, Inception‐ResNet V2, Inception‐V3, ResNet‐101, VGG‐19, VGG‐16, and AlexNet, were trained using our datasets.

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