Feeding video frames into a trained neural network for inference
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Updated
Feb 9, 2020 - Jupyter Notebook
Feeding video frames into a trained neural network for inference
Smile App mimics a person's emotions, age, and gender from CAM, Video, and Picture and sends data to the MQTT broker. In the frontend, Smile is changing real-time
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License plate text extraction using Yolov5 pre-trained model
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Bachelor Thesis in Telecommunication Technologies Engineering.
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building a model to classify the emotion of an image face: Angry, Disgust, Fear, happy, Sad, Surprise, Neutral.
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Waste sorter for recycling using AI
The concept of the project is to generate Arabic captions from the Arabic Flickr8K dataset, the tools that were used are the pre-trained CNN (MobileNet-V2) and the LSTM model, in addition to a set of steps using the NLP. The aim of the project is to create a solid ground and very initial steps in order to help children with learning difficulties.
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