Popular GitHub Repositories for Addition

A set of simple tools for splitting, merging, OP deletion, size compression, rewriting attributes and constants, OP generation, change opset, change to the specified input order, addition of OP, RGB to BGR conversion, change batch size, batch rename of OP, and JSON convertion for ONNX models.

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic E

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

Steering Llama 2 with Contrastive Activation Addition

Using the TextSoundSaver application, you can convert text into realistic synthesized speech. The app achieves smooth and natural text-to-speech conversion. In addition to providing excellent voice synthesis capabilities, the application also allows you to easily export fine-tuned audio files.

A Streamlit powered GPT-3 Application that allows you to chat with tabular data. In addition to AI Chart creation, insights are given too.

This is a hand gesture recognition program that replaces the entire MediaPipe process with ONNX. Simultaneous detection of multiple palms and a simple tracker are additionally implemented. In addition, a simple MLP can learn and recognize gestures.

Reference github repository for the paper "Improving Single-Image Defocus Deblurring: How Dual-Pixel Images Help Through Multi-Task Learning". We propose a single-image deblurring network that incorporates the two sub-aperture views into a multitask framework. Specifically, we show that jointly learning to predict the two DP views from a single blurry input image improves the network’s ability to learn to deblur the image. Our experiments show this multi-task strategy achieves +1dB PSNR improvement over state-of-the-art defocus deblurring methods. In addition, our multi-task framework allows accurate DP-view synthesis (e.g., ~ 39dB PSNR) from the single input image. These high-quality DP views can be used for other DP-based applications, such as reflection removal. As part of this effort, we have captured a new dataset of 7,059 high-quali

This repo deals with time series prediction using LSTMs. An encoder-decoder architecture was used for this purpose. A dual-stage attention mechanism (DA-RNN) has been used in addition to it.

rasa_contrib is a addon package for rasa. It provide some useful/powerful addition components

Preschool evaluation is crucial because it gives teachers and parents influential knowledge about children's growth and development. The COVID-19 pandemic has highlighted the necessity of online assessment for preschool children. One of the areas that should be tested is their ability to speak. Employing an Automatic Speech Recognition (ASR) system would not help since they are pre-trained on voices that differ from children's in terms of frequency and amplitude. Because most of these are pre-trained with data in a specific range of amplitude, their objectives do not make them ready for voices in different amplitudes. To overcome this issue, we added a new objective to the masking objective of the Wav2Vec 2.0 model called Random Frequency Pitch (RFP). In addition, we used our newly introduced dataset to fine-tune our model for Meaningless

The project aims to evaluate the vulnerability of Federated Learning systems to targeted data poisoning attack known as Label Flipping Attack. The project studies the scenario that a malicious participant can only manipulate the raw training data on their device. Hence, non-expert malicious participants can achieve poisoning without knowing the model type, the parameters, and the Federated Learning process. In addition, the project also analyses the possibility and effectiveness of concealing the tracks while poisoning the raw data of other devices.

IFTG (ImageFromTextGenerator) is a Python package that simplifies creating robust datasets for OCR models. Generate images from text, apply over 10 built-in noise effects, and customize fonts and layouts. IFTG supports all languages and offers endless noise combinations, including custom noise creation.

A JAX implementation of stochastic addition.

In this project, I used a deep neural network (built with Keras) to clone car driving behavior. The dataset used to train the network is generated from Udacity's Self-Driving Car Simulator, and it consists of images taken from three different camera angles (Center - Left - Right), in addition to the steering angle, throttle, brake, and speed during each frame. The network is based on NVIDIA's paper End to End Learning for Self-Driving Cars, which has been proven to work in this problem domain.

Test whether the "focus" mechanism is a valuable addition to attention

Blenderset is tool for creating synthetic training data using blender. It can be used to create random scenes consisting of a real background image, ontop of which random humans and vehicles models are rendered with random lighting. In addition to the rendered images, annotations are generated in form of pixelwise instance-segmentations and bounding boxes.

Unreal Engine 4 plugin for Real-Time Multiagent Pathfinding that supports agents with different shapes and velocities, realtime goal updates and agents addition/removal

The main objective is to develop a transportation application using historical Dublin bus and weather data to present an accurate prediction for the users of Dublin bus (ex. an estimate how long it takes to get from point A to point B). However, there is many more considerations to the model such as holidays, traffic, time of year, etc. In addition to the machine learning model, the application is required to work for web and mobile use.

We explores humor generation using GPT-3 by modeling human comedy writing theory and leveraging step-by-step thinking instructions. In addition, we explore the role of cognitive distance in creating humor. Our findings suggest that GPT-3's ability to generate humor can be significantly improved by theory-driven step-by-step thinking instructions.