Artificial Intelligence && Deep Learning
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Channel for who have a passion for -
* Artificial Intelligence
* Machine Learning
* Deep Learning
* Data Science
* Computer vision
* Image Processing
* Research Papers

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Join the channel of researchers and programmers, the channel includes a huge encyclopedia of programming books and scientific articles in addition to the most famous scientific projects

t.me/datascience_books
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NeurIPS 2021—10 papers you shouldn’t miss

2334 papers, 60 workshops, 8 keynote speakers, 15k+ attendees. A dense landscape that’s hard to navigate without a good guide and map, so here are some of our ideas!

https://towardsdatascience.com/neurips-2021-10-papers-you-shouldnt-miss-80f9c0793a3a

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@deeplearning_ai
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Dive into Deep Learning

Interactive deep learning book with code, math, and discussions

Implemented with NumPy/MXNet, PyTorch, and TensorFlow

Adopted at 300 universities from 55 countries

@deeplearning_ai
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Papers with Code 2021 : A Year in Review.

Papers with Code indexes various machine learning artifacts — papers, code, results — to facilitate discovery and comparison. Using this data we can get a sense of what the ML community found useful and interesting this year. Below we summarize the top trending papers, libraries and datasets for 2021 on Papers with Code.

https://medium.com/paperswithcode/papers-with-code-2021-a-year-in-review-de75d5a77b8b

👉👉@deeplearning_ai
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—————— ConvNeXt ——————--


Facebook propose ConvNeXt, a pure ConvNet model constructed entirely from standard ConvNet modules. ConvNeXt is accurate, efficient, scalable and very simple in design.

Github: https://github.com/facebookresearch/ConvNeXt

Paper: https://arxiv.org/abs/2201.03545

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@deeplearning_ai
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#—————CVPR_2021—————


RefineMask: Towards High-Quality Instance Segmentation
with Fine-Grained Features (CVPR 2021)

[paper]
: download paper and enjoy

source: use source code and get awesome result

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321 Open Source Pytorch Implementation Software Projects
Free and open source pytorch implementation code projects including engines, APIs, generators, and tools.

https://opensourcelibs.com/libs/pytorch-implementation

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t.me/MachineLearning_Programming

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Want to jump ahead in artificial intelligence and/or digital pathology? Excited to share that after 2+ years of development PathML 2.0 is out! An open source #computational #pathology software library created by Dana-Farber Cancer Institute/Harvard Medical School and Weill Cornell Medicine led by Massimo Loda to lower the barrier to entry to #digitalpathology and #artificialintelligence , and streamline all #imageanalysis or #deeplearning workflows.

Code: https://github.com/Dana-Farber-AIOS/pathml
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Multi Task Learning for 3D segmentation

Perception stack of an Autonomous Driving system often contains multiple neural networks working together to predict bounding boxes, segmentation maps, depth maps, lane lines etc. Having a separate neural network for each task creates an heavy impact on system's processing speed.

https://github.com/adithyagaurav/Multi_Task_Learning


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@Deeplearning_ai
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Realtime Object-aware Monocular Depth Estimation in Onboard Systems

Video Paper Bibtex

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@Deeplearning_ai
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FLAG: Flow-based 3D Avatar Generation
from Sparse Observations
.

𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
FLow-based Avatar Generative
Conditional distro of body pose
Exact pose likelihood process
Invertibility -> oracle latent code

[PAPER] [Project Page]


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@Deeplearning_ai
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