A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch
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Updated
Sep 5, 2020 - Python
A minimum unofficial implementation of the "A Convolutional Recurrent Neural Network for Real-Time Speech Enhancement" (CRN) using PyTorch
This repositary contain all my exercises and projects of Udacity Computer Vision Nanodegree Program
For sequence-to-sequence beginners. PyTorch-implemented 1DCNN, LSTM, Attention, and Transformers.
Contains additional materials for two keras.io blog posts.
16 projects in the framework of Computer Vision algorithms: 16 projects in the framework of Computer Vision algorithms: CNN, RNN, LSTM, Facial KeyPoints, Image Captioning, SLAM, Edge Detectors, Day Night Classifier, etc.
This project aims to assist visually impaired individuals by providing a solution to convert images into spoken language. Leveraging deep learning and natural language processing, the system processes images, generates descriptive captions, and converts these captions into audio output.
A hybrid CNN-RNN model trained on the DEAM dataset for music emotion recognition using the valence-arousal model. Useful for tagging emotional content of music in media or recommendation systems
Caption generation through a CNN-RNN model further to be converted to speech using a text to speech library for a visually challenged person for understanding the content of an image in the form of speech.
Tuning, training, and transfer learning CRNN models for handwritten text words.
A WebApp that Generates Caption for Images using CNN-RNN Architecture
This project builds a video classification model using CNNs for spatial feature extraction and RNNs for temporal sequence modeling. Utilizing the UCF101 dataset, it covers data preprocessing, feature extraction, model training, and evaluation, providing a comprehensive approach to action recognition in videos.
Transform TV control with Gesture Recognition! Enable intuitive interaction with smart TVs using gestures built using Conv3D, CNN & RNN
Image Captioning using CNN-RNN architecture made with ❤️ in Pytorch. Do 🌟 he repo if you find it useful 🚀
A Deep Learning-based approach to classify human gestures for smart appliances.
A collection of Sentiment Analysis models developed using PyTorch
This repository contains my end-to-end hands-on Deep Learning learning journey, where I implemented core deep learning concepts from scratch and using Keras/TensorFlow. Each notebook focuses on a single concept, building intuition through experiments, visualizations, and practical implementations.
To develop gesture recognition feature for smart TV which help user control the TV without using remote.
Built a CNN-RNN neural network architecture to automatically generate captions from images describing that image.
(50.040) Natural Language Processing
scene text detection
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