lock mechanism with face recognition and liveness detection
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Updated
Sep 7, 2023 - Python
lock mechanism with face recognition and liveness detection
Repository processes CT scanned images of human Lungs , which are in DICOM image format. Visualises the data in 3D and trains a 3D convolution network on the data after preprocessing.
My experimentation around action recognition in videos. Contains Keras implementation for C3D network based on original paper "Learning Spatiotemporal Features with 3D Convolutional Networks", Tran et al. and it includes video processing pipelines coded using mPyPl package. Model is being benchmarked on popular UCF101 dataset and achieves result…
An experimental project for autonomous vehicle driving perception with steering angle prediction and semantic segmentation using a combination of UNet, attention and transformers.
Gender classification on 3D IXI Brain MRI dataset with Keras and Tensorflow
Experiments for the article "A Comparison of Neural Networks for Sign Language Recognition with LSA64" (JCC 2021)
A Simple Three Dimensional Convolutional Neural Networks approach
Data science Mini projects
Transform TV control with Gesture Recognition! Enable intuitive interaction with smart TVs using gestures built using Conv3D, CNN & RNN
The objective of this project is to recognize hand gestures using state-of-the-art neural networks.
Hand Gesture Recognition using Deep Learning Framework
A python class compatible with TensorFlow to perform data augmentation on 3D objects during CNN training.
My team partner and I did this project where we developed a feature in a company’s smart TV that can recognise five different predetermined gestures performed by the user, which will help users control the TV without using a remote.
Imagine you are working as a data scientist at a home electronics company which manufactures state of the art smart televisions. You want to develop a cool feature in the smart-TV that can recognize five different gestures performed by the user which will help users control the TV without using a remote.
Develop a cool feature in the smart-TV that can recognise five different gestures performed by the user which will help users control the TV without using a remote.
Develop a conv3D model that can recognise five different gestures performed by the user which will help users control the TV without using a remote
Fight Detection From Surveillance Cameras by fine-tuning a PyTorch Pretrained Model
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