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GitHub topics: featurefusion

Vibhuarvind/Detection-of-Depression-Using-Late-Fusion-of-Sequential-Actigraphy-Features 📦

Analyzed time-series data (Depressjon) to detect depression from patient activity recorded via clinical actigraphy watches. Utilized features such as time domain, statistical metrics, and LSTM-extracted attributes.

Language: Jupyter Notebook - Size: 1.14 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 0 - Forks: 0

maddy023/multiscale-cnn-keras

MultiScale_FeatureFusion CNN model with keras_2020

Language: Python - Size: 2.93 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 1

maddy023/MultiScale-PreTrained-Models-with-keras-2020

Size: 1000 Bytes - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 0 - Forks: 0

Related Keywords
featurefusion 3 python 2 mutlicnn 2 keras 2 ai 2 pretrained 1 multiscalecnn 1 multiscale 1 models 1 deeplearning 1 colab 1 mutliscale 1 featureextraction 1 dl 1 deeplearing 1 cnn 1 votingcl 1 timedomain 1 time-series-analysis 1 svc 1 statistical-inference 1 stacking-classifier 1 sleep-tracker 1 lstm 1 latefusion 1 depression-detection 1 behavioural 1 adaboost 1