D-Drone_v2 VS Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment

Compare D-Drone_v2 vs Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment and see what are their differences.

Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment

This project is part of the CS course 'Systems Engineering Meets Life Sciences I' at Goethe University Frankfurt. In this Computer Vision project, we present our first attempt at tackling the problem of traffic sign recognition using a systems engineering approach. (by alen-smajic)
InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
D-Drone_v2 Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment
1 2
10 45
- -
10.0 0.0
almost 2 years ago almost 3 years ago
Jupyter Notebook C#
GNU General Public License v3.0 only MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

D-Drone_v2

Posts with mentions or reviews of D-Drone_v2. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-08.

Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment

Posts with mentions or reviews of Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing D-Drone_v2 and Towards-Explainable-AI-System-for-Traffic-Sign-Recognition-and-Deployment-in-a-Simulated-Environment you can also consider the following projects:

SeeAI - Enabling computers to perform NLP on data obtained from advanced computer vision

flowframes - Flowframes Windows GUI for video interpolation using DAIN (NCNN) or RIFE (CUDA/NCNN)

Human-pose-estimation - A quick tutorial on multi-pose estimation with OpenCV, Tensorflow and MoveNet lightning.

OpenSeeFace - Robust realtime face and facial landmark tracking on CPU with Unity integration

uav-detection - Drone / Unmanned Aerial Vehicle (UAV) Detection is a very safety critical project. It takes in Infrared (IR) video streams and detects drones in it with high accuracy.

Alturos.Yolo - C# Yolo Darknet Wrapper (real-time object detection)

samples - WebRTC Web demos and samples

com.unity.perception - Perception toolkit for sim2real training and validation in Unity

ailab - Experience, Learn and Code the latest breakthrough innovations with Microsoft AI

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning - My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset.

3D-Public-Transport-Simulator - The 3D Public Transport Simulator is a Unity-based simulation, which uses OpenStreetMap data in order to support the simulation of worldwide locations. The development was part of a Bachelor thesis.

caer - High-performance Vision library in Python. Scale your research, not boilerplate.