Computer Science and Programming

前往频道在 Telegram

Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_science

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网络:Computer Science and Programming 意大利88 技术与应用811...

📈 Telegram 频道 Computer Science and Programming 的分析概览

频道 Computer Science and Programming (@computer_science_and_programming) 英语语言赛道中的是活跃参与者。目前社区聚集了 140 416 名订阅者，在 技术与应用 类别中位列第 811，并在 意大利 地区排名第 88 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 140 416 名订阅者。

根据 01 九月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 -772，过去 24 小时变化为 -64，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 8.15%。内容发布后 24 小时内通常能获得 1.97% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 11 442 次浏览，首日通常累积 2 771 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 13。
主题关注点： 内容集中在 sellerflash, github, developer, pricing, waybienad 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Channel specialized for advanced topics of: * Artificial intelligence, * Machine Learning, * Deep Learning, * Computer Vision, * Data Science * Python Admin: @otchebuch Memes: @memes_programming Ads: @Source_Ads, https://telega.io/c/computer_sc...”

凭借高频更新（最新数据采集于 02 九月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

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140 416

订阅者

-6424 小时

-2617 天

-77230 天

11 442

帖子浏览量

~ 2 77124 小时

~ 3 80448 小时

8.15%

参与率

无数据

每日帖子数

Ads index

beta

帖子存档

140 416

It's CVPR time! We will not meet in person next week at CVPR 2020 Seattle: The conference has gone virtual...

140 416

sticker.webp0.16 KB

140 416

Github link of "AI DeOldify Tool": https://github.com/jantic/DeOldify?fbclid=IwAR2-glzM1UYuWHJWuNKi741bm8aeofZdE1-0v9ZN-6Lmlmh4ta63mn5ydZc —————————————————————————— Masked face recognition dataset👇 Wolrd’s most complete Masked Face Recognition Dataset is Free to Download: https://medium.com/the-programming-hub/wolrds-most-complete-masked-face-recognition-dataset-is-for-free-10d780eed512 ——————————————————————————

140 416

You Can Color Your Grandparent's Old Pictures or Videos with AI DeOldify Tool

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Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models Paper: https://arxiv.org/pdf/2005.07310.pdf Related Codes: https://github.com/airsplay/lxmert https://github.com/ChenRocks/UNITER

140 416

Short over view of Artificial Neural Networks with examples Page: https://www.infinitycodex.in/

140 416

Content-based Image retrieval Paper: https://arxiv.org/abs/2005.02154 Github: https://github.com/PyRetri/PyRetri Installation: https://github.com/PyRetri/PyRetri/blob/master/docs/INSTALL.md

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PyRetri: An open source deep learning based unsupervised image retrieval toolbox built on PyTorch🔥

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https://paperswithcode.com/conference/iclr-2020-1/official?fbclid=IwAR0IHbPMDciaoEtbFdVyqrNtkjCOWmL5vdevMdaONJl2-HkR_q1L4U26AtI

140 416

ICLR 2020 (International Conference on Learning Representations) papers and their codes. Papers ranked based on stars

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CVPR 2020 Paper: https://arxiv.org/abs/2004.01180 Project Page: https://www.cmlab.csie.ntu.edu.tw/~yulunliu/ObstructionRemoval Github: https://github.com/alex04072000/ObstructionRemoval

140 416

Learning to See Through Obstructions

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MIT Media Lab https://aieducation.mit.edu/resources

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AI Literacy for K-12 School Children

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3D Photography using Context-aware Layered Depth Inpainting

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Paper: https://drive.google.com/file/d/17ki_YAL1k5CaHHP3pIBFWvw-ztF4CCPP/view Github: https://github.com/vt-vl-lab/3d-photo-inpainting Project: https://shihmengli.github.io/3D-Photo-Inpainting/ Notebook: https://colab.research.google.com/drive/1706ToQrkIZshRSJSHvZ1RuCiM__YX3Bz

140 416

Tasks under Unsupervised learning: https://www.infinitycodex.in/ Deep Unsupervised Learning: Lecture: https://youtu.be/JBb5sSC0JoY Slides: https://bit.ly/34dVGE1 Colab: https://bit.ly/2JEzsl1

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Important Tasks under Unsupervised Learning: Clustering Anomaly detection Dimensionality reduction and CS294-158 Deep Unsupervised Learning from Abbeel et al.

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Article link: https://arxiv.org/ftp/arxiv/papers/2002/2002.06177.pdf