Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
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Mar 1, 2024 - Jupyter Notebook
Deep Learning and Machine Learning stocks represent promising opportunities for both long-term and short-term investors and traders.
🔉 spafe: Simplified Python Audio Features Extraction
[CVPR] MARLIN: Masked Autoencoder for facial video Representation LearnINg
Kaldi-compatible online & offline feature extraction with PyTorch, supporting CUDA, batch processing, chunk processing, and autograd - Provide C++ & Python API
EntroPy: complexity of time-series in Python (DEPRECATED)
Deep learning methods for feature selection in gene expression autism data.
An in-depth tutorial on the theory of panorama stitching
Problem Statement: Given the tweets from customers about various tech firms who manufacture and sell mobiles, computers, laptops, etc, the task is to identify if the tweets have a negative sentiment towards such companies or products.
Code for paper 'Avoid touching your face: A hand-to-face 3d motion dataset (covid-away) and trained models for smartwatches'
FeatTS is a Semi-Supervised Clustering method that leverages features extracted from the raw time series to create clusters that reflect the original time series.
Cloud-Assisted Multi-View Video Summarization using CNN and Bi-Directional LSTM
Learnable STRF, from Riad et al. 2021 JASA
Python Open-source package for medical images processing and radiomics features extraction.
LibSA4Py: Light-weight static analysis for extracting type hints and features
Codes for the paper "A Robust Of-line Writer Identification Method" in ACTA AUTOMATICA SINICA, 2020
The project addresses automatic detection of microaneurysms (MA) which are first detectable changes in Diabetic Retinopathy (DR). Green channel, being the most contrasted channel, of the color fundus images are considered. The algorithm includes pre-processing, MA candidates detection, features extraction, classification and comparison with grou…
Awesome papers on Feature Extraction (Dimensionality Reduction)
Spatio-temporal features extraction that measure the stabilty. The proposed method is based on a compression algorithm named Run Length Encoding. The workflow of the method is presented bellow.
[IN PROGRESS] Multimodal feature extraction modules for ease of doing research and reproducibility.
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