⬅️📽️ App inspired by Windows Recall for creating duplicate screenshots with text recognition and the ability to search through screenshots.
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Updated
Jun 22, 2024 - Python
⬅️📽️ App inspired by Windows Recall for creating duplicate screenshots with text recognition and the ability to search through screenshots.
OpenRecall is a fully open-source, privacy-first alternative to proprietary solutions like Microsoft's Windows Recall. With OpenRecall, you can easily access your digital history, enhancing your memory and productivity without compromising your privacy.
This is an open surce alternative at microsof recall and at OpenRecall (sorry... but OpenRecall isn't working on my waylnad KDE Arhc linux)
Testing the consistency of binary classification performance scores reported in papers
Take screenshots every few mins and browse your "work sessions"
This project predicts diabetes using the PIMA Diabetes dataset, leveraging health metrics of Pima Indian women. Machine learning models like Logistic Regression, Decision Trees, and Random Forest are implemented to determine the likelihood of diabetes, evaluated using metrics like accuracy, precision, recall, F1-score, and ROC-AUC.
Welcome to **LiveRecall**, the open-source alternative to Microsoft's Recall. LiveRecall captures snapshots of your screen and allows you to recall them using natural language queries, leveraging semantic search technology. For added security, all images are encrypted.
The proposed algorithm calculates the Initial Recall value of the Dataset. It eliminates least correlated features using the Correlation Matrix. Using Gaussian Curve, for all the columns it identifies and eliminates rows having values which lie beyond (µ ± 3σ).
Comparing the performance of MLP (multilayer perceptron) and CNN (convolutional neural network) on USPS dataset and visualizing it via TensorBoard.
This tool extracts and displays data from the Recall feature in Windows 11, providing an easy way to access information about your PC's activity snapshots.
Comparing logistic regression, decision tree, random forest, k-nearest neighbors, and SVMs in regard to binary prediction performance metrics.
Best for beginners | Well explained ML algorithms | organized Notebooks | Case Studies
Recall for KSP blunders, screw ups and borks.
Directing Sentiment and Evoking Recall in GPT-2 from an Attention Bock Based Persistent Memory using a Small Fraction of One Layer and a Case for the Spacial Separation of what might be described as Emotional Implicit Memory and Explicit Memory
Text-based sentiment analysis plays a very important role in understanding customer opinions and preferences. But despite extensive research in sentiment and emotion analysis in text, a notable gap exists in understanding code-mixed texts. To address this, we propose an end-to-end transformer based model.
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