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uukssw/quote1/from_customer/Ai Lidar/Source_Code.ipynb
louiscklaw b79d5bc270 update,
2025-02-01 02:10:34 +08:00

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{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": []
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
}
},
"cells": [
{
"cell_type": "code",
"source": [
"Model training (main_reference)\n",
"https://github.com/YJZFlora/Fall_Detection_Deep_Learning_Model/blob/master/Training_code/model_training_May08.ipynb"
],
"metadata": {
"id": "zHyR_1L8Mugk"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "83l_uzqfMKRk"
},
"outputs": [],
"source": [
"Openpose\n",
"https://github.com/CMU-Perceptual-Computing-Lab/\n",
"openpose\n",
"\n",
"Real-time\n",
"https://github.com/tonlongthuat/Real-Time-Fall-Detection\n",
"\n",
"Load data reference\n",
"https://github.com/ManniArtivor24/Fall-Detection/blob/main/Major%20Project%20Fall%20detection%20Notebook.ipynb\n",
"\n",
"Pose-based vs Image-based\n",
"https://github.com/ryankemmer/FallDetection/blob/master/FallDetection_Pose_Based_Models.ipynb\n",
"\n",
"LSTM teansfer learn\n",
"https://github.com/IKKIM00/fall-detection-and-predction-using-GRU-and-LSTM-with-Transfer-Learning/blob/master/SmartFall_LSTM_Classification.ipynb"
]
}
]
}