Popular GitHub Repositories for Aircraft Inspection

A library for debugging/inspecting machine learning classifiers and explaining their predictions

This project proposes an end-to-end framework for semi-supervised Anomaly Detection and Segmentation in images based on Deep Learning.

Image anomaly detection benchmark in industrial manufacturing

A deep generative model to predict aircraft actual trajectories using high dimensional weather data

I have built the computer vision models in 3 different ways addressing different personas, because not all companies will have a resolute data science team. quality-control manufacturing big-data-analytics jupyter-notebook cognitive services industry solutions

AI - a simple commandline local/remote LLM chat client. Supports any local or remote OpenAI-compatible API endpoint (GPT4o, Gemini, Grok, OpenRouter, Ollama, LM Studio and more), model management, multiple conversations support, automatic topic identification, image generation using Dall-E and stdin piping (sending files to LLM for inspection)

Collection of works in my PhD at Virginia Tech, mostly focused on computer vision and machine learning applications in structural inspection and structural health monitoring.

Application of LSTM network for Structural Health Monitoring & Non-Destructive Testing

[ECCV 2024] Official Implementation of An Incremental Unified Framework for Small Defect Inspection

A plugin that adds first-class support for Project Jimmer

Officiel implementation of the paper "FlightScope: An Experimental Comparative Review of Aircraft Detection Algorithms in Satellite Imagery"

Aircraft engine failure prediction model

Autoencoder t-SNE for anomaly detection in aircraft trajectories

Document Filters is an SDK for applications like content indexing, e-discovery, data migration, and feeding data into AI/ML models by extracting data from unstructured sources. It gives the ability to perform deep inspection, data extraction, output manipulation, and conversion for virtually any type of document, in any programming language.

This repo contains implementation of deep learning-based steel surface defect segmentation models. Extensive experiments on several deep learning frameworks have been presented with various performance analysis and comparison.

The code for "Self-supervised Context Learning for Visual Inspection of Industrial Defects"

PyTorch implementation of RIC for conveyor systems with Deep Q-Networks (DQN) and Profit-Sharing (PS). Wang, T., Cheng, J., Yang, Y., Esposito, C., Snoussi, H., & Tao, F. (2020). Adaptive Optimization Method in Digital Twin Conveyor Systems via Range-Inspection Control. IEEE Transactions on Automation Science and Engineering.

A pill quality control dataset and associated anomaly detection example

FedGrad: Mitigating Backdoor Attacks in Federated Learning through Local Ultimate Gradients Inspection (IJCNN 2023)

Anomaly detected using aerial imagery can be of many types like unknown ship in docks, or a unidentified aircraft at the airport and other similar anomalies. In this project we've mainly focused on ship dataset to detect all the ships in a waterbody using keras-retinanet.