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 With advertising offers contact:

India6 003 Technologies & Applications2 289...

📈 Analytical overview of Telegram channel Artificial Intelligence && Deep Learning

Channel Artificial Intelligence && Deep Learning (@deeplearning_ai) in the English language segment is an active participant. Currently, the community unites 58 023 subscribers, ranking 2 289 in the Technologies & Applications category and 6 003 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 58 023 subscribers.

According to the latest data from 24 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -193 over the last 30 days and by 17 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 9.42%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
Post reach: On average, each post receives 5 467 views. Within the first day, a publication typically gains 0 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 16.
Thematic interests: Content is focused on key topics such as github, learning, estimation, dataset, engineer.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Channel for who have a passion for - * Artificial Intelligence * Machine Learning * Deep Learning * Data Science * Computer vision * Image Processing * Research Papers With advertising offers contact:”

Thanks to the high frequency of updates (latest data received on 25 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

58 023

Subscribers

+1724 hours

-237 days

-19330 days

5 467

Post views

No data24 hours

No data48 hours

9.42%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

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Hierarchical Multi-Scale Attention for Semantic Segmentation PyTorch implementation Github: https://github.com/NVIDIA/semantic-segmentation Video: https://www.youtube.com/watch?v=odAGA7pFBGA&feature=youtu.be Paper: https://arxiv.org/abs/2005.10821 Method Details: https://www.cityscapes-dataset.com/method-details/?submissionID=7836

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Multi-scale inference is commonly used to improve the results of semantic segmentation. combining multi-scale predictions. it to be roughly 4x more memory efficient to train than other recent approaches. In addition to enabling faster training, this allows us to train with larger crop sizes which leads to greater model accuracy.

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The top 10 computer vision papers in 2020 with video demos, articles, code, and paper reference. https://www.kdnuggets.com/2021/01/top-10-computer-vision-papers-2020.html Join: https://t.me/DeepLearning_ai

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Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net https://deepai.org/publication/fast-and-furious-real-time-end-to-end-3d-detection-tracking-and-motion-forecasting-with-a-single-convolutional-net Join: https://t.me/DeepLearning_ai

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Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net

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Real-Time Lane Detection and alerts for Autonomous Driving medium: https://towardsdatascience.com/real-time-lane-detection-and-alerts-for-autonomous-driving-1f0a021390ee paper: https://arxiv.org/pdf/1807.01726.pdf github repo: https://github.com/MaybeShewill-CV/lanenet-lane-detection Join: https://t.me/DeepLearning_ai

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Lane-Detection

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Link of those books : https://bit.ly/2HXmaTK join: https://t.me/DeepLearning_ai

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Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Paper: https://compvis.github.io/net2net/ source codes: https://github.com/CompVis/net2net?utm_source=Deep+Learning+Weekly&utm_campaign=b85cddf829-EMAIL_CAMPAIGN_2019_04_24_03_18_COPY_01&utm_medium=email&utm_term=0_384567b42d-b85cddf829-156293989 join: https://t.me/DeepLearning_ai

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NeurIPS 2020 NeurIPS (Neural Information Processing Systems), the largest machine learning and computational neuroscience conference will be held online on Dec 6-12. https://crossminds.ai/explore/ join: https://t.me/DeepLearning_ai https://t.me/MachineLearning_Programming

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The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. 1. https://lnkd.in/dXZWGUG 2. https://icml.cc/ 3. https://t.me/DeepLearning_ai

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4 Top AI/ML Github Repositories in November 2020 1. PIFuHD: Multi-Level Pixel-Aligned Implicit Function for High-Resolution 3D Human Digitization: 2,558 Stars 2. Microsoft: Bring Old Photos Back To Life: 2892 Stars 3. Project Sherlock: 1952 Stars 1. https://towardsdatascience.com/4-top-ai-ml-github-repositories-in-november-2020-aa51656aaab9 2. https://t.me/DeepLearning_ai

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