اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Artificial Intelligence && Deep Learning
رفتن به کانال در Telegram
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:
نمایش بیشتر📈 تحلیل کانال تلگرام Artificial Intelligence && Deep Learning
کانال Artificial Intelligence && Deep Learning (@deeplearning_ai) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 58 015 مشترک است و جایگاه 2 295 را در دسته فناوری و برنامهها و رتبه 6 034 را در منطقه الهند دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 58 015 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 22 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -213 و در ۲۴ ساعت گذشته برابر -3 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 8.63% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً N/A% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 5 007 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 14 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند github, learning, estimation, dataset, engineer تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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:”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 23 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
58 015
مشترکین
-324 ساعت
-537 روز
-21330 روز
آرشیو پست ها
Repost from Machine Learning with Python
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This channels is for Programmers, Coders, Software Engineers.
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🌟 Discover 6DRepNet: The Ultimate Head Pose Estimation Model!
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* Easy setup with Conda
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Watch the performance showcase on GitHub for future advancements.
[Source Code] [Paper]
join our community:
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🌟 Discover 6DRepNet: The Ultimate Head Pose Estimation Model!
Features:
* State-of-the-art accuracy
* Comprehensive tools for training, testing, and inference
* Easy setup with Conda
* Supports multiple datasets
Watch the performance showcase on GitHub for future advancements.
[Source Code] [Paper]
join our community:
👉 @deeplearning_ai
🆔🆔 Magic-Me: Identity-Specific Video 🆔🆔
👉hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 💙
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hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
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👉Paper https://arxiv.org/pdf/2402.09368.pdf
👉Project https://magic-me-webpage.github.io/
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🆔🆔 Magic-Me: Identity-Specific Video 🆔🆔
👉hashtag#ByteDance (+UC Berkeley) unveils VCD for video-gen: with just a few images of a specific identity it can generate temporal consistent videos aligned with the given prompt. Impressive results, source code under Apache 2.0 💙
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Novel Video Custom Diffusion (VCD) framework
✅High-Quality ID-specific videos generation
✅Improvement in aligning IDs-images and text
✅Robust 3D Gaussian Noise Prior for denoising
✅Better Inter-frame correlation / video consistency
✅New modules F-VCD/T-VCD for videos upscale
✅New train with masked loss by prompt-to-segmentation
hashtag#artificialintelligence hashtag#machinelearning hashtag#ml hashtag#AI hashtag#deeplearning hashtag#computervision hashtag#AIwithPapers hashtag#metaverse
👉Channel: @deeplearning_ai
👉Paper https://lnkd.in/df57pbXR
👉Project https://lnkd.in/dKy_cy3u
👉Code https://lnkd.in/dwMfUFH3
EfficientViT - SAM:69x Faster SAM: Multi-Scale Linear Attention for High-Resolution Dense Prediction
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3. Paper: https://arxiv.org/abs/2402.05008
This channels is for Programmers, Coders, Software Engineers.
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Awesome-AIGC-3D
A curated list of awesome AIGC 3D papers, inspired by awesome-NeRF.
Source code: https://github.com/hitcslj/awesome-aigc-3d?tab=readme-ov-file
Awesome-AIGC-3D
A curated list of awesome AIGC 3D papers, inspired by awesome-NeRF.
Source code: https://github.com/hitcslj/awesome-aigc-3d?tab=readme-ov-file
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PhotoMaker: Customizing Realistic Human Photos via Stacked ID Embedding
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Open-Vocabulary SAM
[Paper] [Project Page] [Hugging Face Demo]
Source Code: https://github.com/harboryuan/ovsam?tab=readme-ov-file
