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Top 23 Convolution Open-Source Projects
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MNN
MNN is a blazing fast, lightweight deep learning framework, battle-tested by business-critical use cases in Alibaba
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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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RootlessJamesDSP
An implementation of the system-wide JamesDSP audio processing engine for non-rooted Android devices
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JamesDSPManager
Audio DSP effects build on Android system framework layer. This is a repository contains a pack of high quality DSP algorithms specialized for audio processing.
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rocket
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels (by angus924)
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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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laser
The HPC toolbox: fused matrix multiplication, convolution, data-parallel strided tensor primitives, OpenMP facilities, SIMD, JIT Assembler, CPU detection, state-of-the-art vectorized BLAS for floats and integers (by mratsim)
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convolution-vision-transformers
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
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CoordConv
Pytorch implementation of "An intriguing failing of convolutional neural networks and the CoordConv solution" - https://arxiv.org/abs/1807.03247 (by walsvid)
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pyTsetlinMachine
Implements the Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, Weighted Tsetlin Machine, and Embedding Tsetlin Machine, with support for continuous features, multigranularity, clause indexing, and literal budget
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tmu
Implements the Tsetlin Machine, Coalesced Tsetlin Machine, Convolutional Tsetlin Machine, Regression Tsetlin Machine, and Weighted Tsetlin Machine, with support for continuous features, drop clause, Type III Feedback, focused negative sampling, multi-task classifier, autoencoder, literal budget, and one-vs-one multi-class classifier. TMU is written in Python with wrappers for C and CUDA-based clause evaluation and updating.
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hydra
HYDRA: Competing convolutional kernels for fast and accurate time series classification (by angus924)
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Convolution-From-Scratch
Implementation of the generalized 2D convolution with dilation from scratch in Python and NumPy
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CNN-Filter-DB
A database of over 1.4 billion 3x3 convolution filters extracted from hundreds of diverse CNN models with relevant meta information (CVPR 2022 ORAL)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
Project mention: [D][R] Deploying deep models on memory constrained devices | /r/MachineLearning | 2023-10-03However, I am looking on this subject through the problem of training/finetuning deep models on the edge devices, being increasingly available thing to do. Looking at tflite, alibaba's MNN, mit-han-lab's tinyengine etc..
Project mention: Seeking advice on monetizing an open-source Golang-based video transcoding project developed during university | /r/golang | 2023-06-04There are a number of projects using manipulation libraries like https://github.com/disintegration/imaging which is already MIT licensed, and then there are various transcoders which I am unfamiliar with, but you will want to consider if you add enough value to make use of those unimportant to the decision to pay.
Project mention: [P] - VkFFT now supports quad precision (double-double) FFT computation on GPU | /r/MachineLearning | 2023-09-27Hello, I am the creator of the VkFFT - GPU Fast Fourier Transform library for Vulkan/CUDA/HIP/OpenCL/Level Zero and Metal. In the latest update, I have added support for quad-precision double-double emulation for FFT calculation on most modern GPUs. I understand that modern ML is going in the opposite low-precision direction, but I still think that it may be useful to have this functionality at least for some prototyping and development of concepts.
Project mention: [Suggestion] Remove screen capture restriction on Spotify | /r/xManagerApp | 2023-12-09
It depends.
You need 2~3 accumulators to saturate instruction-level parallelism with a parallel sum reduction. But the compiler won't do it because it only creates those when the operation is associative, i.e. (a+b)+c = a+(b+c), which is true for integers but not for floats.
There is an escape hatch in -ffast-math.
I have extensive benches on this here: https://github.com/mratsim/laser/blob/master/benchmarks%2Ffp...
Project mention: has anyone here implemented Convolutional Vision Transformer (CvT)? | /r/pytorch | 2023-05-16
Github: https://github.com/NumPower/numpower
Project mention: CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters (CVPR 2022 Oral) | /r/LearningMachines | 2023-07-08Repo & dataset: https://github.com/paulgavrikov/CNN-Filter-DB
Convolution related posts
- [Suggestion] Remove screen capture restriction on Spotify
- Tsetlin machine – the other AI toolbooks
- Tsetlin Machine Unified (TMU) - One Codebase to Rule Them All
- [D][R] Deploying deep models on memory constrained devices
- [P] - VkFFT now supports quad precision (double-double) FFT computation on GPU
- VkFFT now supports quad precision (double-double) FFT computation on GPU
- VkFFT: Vulkan/CUDA/Hip/OpenCL/Level Zero/Metal Fast Fourier Transform Library
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A note from our sponsor - SaaSHub
www.saashub.com | 26 Apr 2024
Index
What are some of the best open-source Convolution projects? This list will help you:
Project | Stars | |
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1 | MNN | 8,293 |
2 | imaging | 5,070 |
3 | VkFFT | 1,441 |
4 | RootlessJamesDSP | 729 |
5 | JamesDSPManager | 462 |
6 | rocket | 399 |
7 | massiv | 382 |
8 | minirocket | 267 |
9 | laser | 261 |
10 | sharpened-cosine-similarity | 247 |
11 | jdsp | 232 |
12 | etl | 211 |
13 | convolution-vision-transformers | 210 |
14 | numpower | 146 |
15 | CoordConv | 141 |
16 | pyTsetlinMachine | 121 |
17 | tmu | 108 |
18 | realbloom | 100 |
19 | hydra | 38 |
20 | Convolution-From-Scratch | 35 |
21 | CNN-Filter-DB | 28 |
22 | image-conv | 8 |
23 | vectorized_convolution | 6 |
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