ENHANCING LOW-RESOLUTION FACIAL RECOGNITION THROUGH DEEP BELIEF NETWORKS AND DENOISING AUTOENCODERS
Budget: $250 – $750 USD
The research needs only review and working on certain notes.
The objectives of the research are:
• To filter and remove noise while preserving important features for improving the quality of low-resolution images by using novel filtering techniques.
• To extract the most important facial features from the low-resolution images using Deep Autoencoder (DAE) for improved classification accuracy.
• To design a low-resolution facial recognition model using a deep learning classifier
NO AGENT MESSAGING PLEASE - WON'T RESPOND
The objectives of the research are:
• To filter and remove noise while preserving important features for improving the quality of low-resolution images by using novel filtering techniques.
• To extract the most important facial features from the low-resolution images using Deep Autoencoder (DAE) for improved classification accuracy.
• To design a low-resolution facial recognition model using a deep learning classifier
NO AGENT MESSAGING PLEASE - WON'T RESPOND