ml-mipt VS Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

Compare ml-mipt vs Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning and see what are their differences.

ml-mipt

Former repository of ML course. Redirect link included (by girafe-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. (by alen-smajic)
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ml-mipt Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning
18 8
8 57
- -
0.0 3.6
over 1 year ago about 3 years ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
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ml-mipt

Posts with mentions or reviews of ml-mipt. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing ml-mipt and Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning you can also consider the following projects:

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mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.

yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x

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HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

Deep-Learning-Computer-Vision - My assignment solutions for Stanford’s CS231n (CNNs for Visual Recognition) and Michigan’s EECS 498-007/598-005 (Deep Learning for Computer Vision), version 2020.

simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper

d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.

NYU-DLSP20 - NYU Deep Learning Spring 2020