Sakib1263/TF-1D-2D-Segmentation-End2EndPipelines

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Updated over 1 year ago

Sakib1263/TF-1D-2D-Segmentation-End2EndPipelines

Sakib1263

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1D and 2D Segmentation Models with options such as Deep Supervision, Guided Attention, BiConvLSTM, Autoencoder, etc.

Inception-InceptionResNet-SEInception-SEInceptionResNet-1D-2D-Tensorflow-Keras

Models Supported: Inception [v1, v2, v3, v4], SE-Inception, Inception_ResNet [v1, v2], SE-Inception_ResNet (1D and 2D version with DEMO for Classification and Regression)

Jupyter Notebook

TF-1D-2D-ResNetV1-2-SEResNet-ResNeXt-SEResNeXt

Models supported: ResNet, ResNetV2, SE-ResNet, ResNeXt, SE-ResNeXt [layers: 18, 34, 50, 101, 152] (1D and 2D versions with DEMO for Classification and Regression).

Jupyter Notebook

NABNet

NABNet: A Nested Attention-guided BiConvLSTM Network for a robust ‎prediction of Blood Pressure components from reconstructed Arterial Blood ‎Pressure waveforms using PPG and ECG Signals

Jupyter Notebook

DenseNet-1D-2D-Tensorflow-Keras

Models Supported: DenseNet121, DenseNet161, DenseNet169, DenseNet201 and DenseNet264 (1D and 2D version with DEMO for Classification and Regression)

Jupyter Notebook

VGG-1D-2D-Tensorflow-Keras

Models Supported: VGG11, VGG13, VGG16, VGG16_v2, VGG19 (1D and 2D versions with DEMO for Classification and Regression).

Jupyter Notebook

MobileNet-1D-2D-Tensorflow-Keras

Supported Models: MobileNet [V1, V2, V3_Small, V3_Large] (Both 1D and 2D versions with DEMO, for Classification and Regression)

Jupyter Notebook

COVID-19-Vaccine-Willingness-and-Hesitancy-among-Residents-in-Qatar

A Machine Learning-based approach to classify COVID-19 Vaccine Willingness and Hesitancy severity among people in Qatar based on survey outcomes.

Jupyter Notebook

Sakib1263

AlbUNet-1D-2D-Tensorflow-Keras

Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)

EfficientNet-1D-2D-Tensorflow-Keras

Models Supported: EfficientNet B0-B7, L2 (Both 1D and 2D Models with DEMO, developed in Tensorflow, Keras)