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

58 023

MediaPipe Objectron MediaPipe Objectron is a mobile real-time 3D object detection solution for everyday objects. It detects objects in 2D images, and estimates their poses through a machine learning (ML) model, trained on the Objectron dataset. https://google.github.io/mediapipe/solutions/objectron.html @deeplearning_ai

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MediaPipe Objectron MediaPipe Objectron is a mobile real-time 3D object detection solution for everyday objects. It detects objects in 2D images, and estimates their poses through a machine learning (ML) model, trained on the Objectron dataset. https://google.github.io/mediapipe/solutions/objectron.html @deeplearning_ai

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Unseen Object Amodal Instance Segmentation (UOAIS)

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Code: https://github.com/gist-ailab/uoais#unseen-object-amodal-instance-segmentation-uoais Paper: https://arxiv.org/abs/2109.11103 Dataset: https://paperswithcode.com/dataset/ocid Project page: https://sites.google.com/view/uoais join us: @deeplearning_ai

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Paper: https://arxiv.org/pdf/2105.06993.pdf Project Page: https://omnimatte.github.io/ Github: https://github.com/erikalu/omnimatte Supplimentary material: https://omnimatte.github.io/supplementary/index.html Explained: https://www.youtube.com/watch?v=lCBSGOwV-_o @deeplearning_ai

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Paper: https://arxiv.org/pdf/2105.06993.pdf Project Page: https://omnimatte.github.io/ Github: https://github.com/erikalu/omnimatte Supplimentary material: https://omnimatte.github.io/supplementary/index.html Explained: https://www.youtube.com/watch?v=lCBSGOwV-_o @deeplearning_ai

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Now removing, duplicating or enhancing objects in video is more realistic with the assist of AI @deeplearning_ai

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Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstruction ICCV 2021 Paper: https://arxiv.org/abs/2109.00512 Github: https://github.com/facebookresearch/co3d Project Page: https://ai.facebook.com/blog/common-objects-in-3d-dataset-for-3d-reconstruction Learn more: https://ai.facebook.com/datasets/CO3D-dataset/ 👉@deeplearning_ai

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SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping Paper: https://arxiv.org/pdf/2105.07014.pdf Video: https://www.youtube.com/watch?v=W7NCbfZp6QE Code: https://github.com/google-research/google-research/tree/master/smurf @deeplearning_ai

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From Google and Waymo researchers: The self-/unsupervised revolution is near! Unsupervised optical flow model SMURF improves SOTA by 40% and beats many supervised methods such as PWC-Net and FlowNet2 @deeplearning_ai

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Top Universities Offering Free Online Programming Courses https://www.naukri.com/learning/articles/top-universities-offering-free-online-courses-for-programmers/ @deeplearning_ai .

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Top Universities Offering Free Online Programming Courses Here’s the list of the top universities offering free online programming courses: Harvard University Massachusetts Institute of Technology (MIT) IIT Bombay University of Illinois Hong Kong University of Science and Technology University of Michigan IIT Kanpur @deeplearning_ai

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