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Top 23 Python convolutional-neural-network Projects
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Pytorch-UNet
PyTorch implementation of the U-Net for image semantic segmentation with high quality images
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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.
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darkflow
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
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image-super-resolution
🔎 Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
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Efficient-AI-Backbones
Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.
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Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials
A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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image-quality-assessment
Convolutional Neural Networks to predict the aesthetic and technical quality of images.
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SparK
[ICLR'23 Spotlight🔥] The first successful BERT/MAE-style pretraining on any convolutional network; Pytorch impl. of "Designing BERT for Convolutional Networks: Sparse and Hierarchical Masked Modeling" (by keyu-tian)
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cnnimageretrieval-pytorch
CNN Image Retrieval in PyTorch: Training and evaluating CNNs for Image Retrieval in PyTorch
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hardnet
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
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Sign-Language-Interpreter-using-Deep-Learning
A sign language interpreter using live video feed from the camera.
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Lifting-from-the-Deep-release
Implementation of "Lifting from the Deep: Convolutional 3D Pose Estimation from a Single Image"
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assembled-cnn
Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"
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SaaSHub
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Project mention: Logistic Regression for Image Classification Using OpenCV | news.ycombinator.com | 2023-12-31In this case there's no advantage to using logistic regression on an image other than the novelty. Logistic regression is excellent for feature explainability, but you can't explain anything from an image.
Traditional classification algorithms but not deep learning such as SVMs and Random Forest perform a lot better on MNIST, up to 97% accuracy compared to the 88% from logistic regression in this post. Check the Original MNIST benchmarks here: http://fashion-mnist.s3-website.eu-central-1.amazonaws.com/#
In Phil tabor's implementation it calculates Actor and Critic loss separately (line 95+) and does not calculate equation 9.
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A note from our sponsor - SaaSHub
www.saashub.com | 25 Apr 2024
Index
What are some of the best open-source convolutional-neural-network projects in Python? This list will help you:
Project | Stars | |
---|---|---|
1 | fashion-mnist | 11,439 |
2 | Pytorch-UNet | 8,358 |
3 | darkflow | 6,131 |
4 | image-super-resolution | 4,493 |
5 | Efficient-AI-Backbones | 3,783 |
6 | Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials | 3,638 |
7 | Super-SloMo | 2,965 |
8 | image-quality-assessment | 2,000 |
9 | dl-4-tsc | 1,447 |
10 | SparK | 1,387 |
11 | cnnimageretrieval-pytorch | 1,375 |
12 | head-pose-estimation | 1,149 |
13 | SincNet | 1,097 |
14 | NeuRec | 1,031 |
15 | PixelLib | 1,013 |
16 | Youtube-Code-Repository | 833 |
17 | sudoku | 819 |
18 | BCDU-Net | 647 |
19 | hardnet | 503 |
20 | Sign-Language-Interpreter-using-Deep-Learning | 461 |
21 | Lifting-from-the-Deep-release | 448 |
22 | assembled-cnn | 330 |
23 | Mask-RCNN-TF2 | 299 |
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