اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
AI with Papers - Artificial Intelligence & Deep Learning
رفتن به کانال در Telegram
All the AI with papers. Every day fresh updates about #DeepLearning #MachineLearning #LLM & #ComputerVision Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/ #AI #chatGPT
نمایش بیشتر📈 تحلیل کانال تلگرام AI with Papers - Artificial Intelligence & Deep Learning
کانال AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 17 168 مشترک است و جایگاه 7 718 را در دسته فناوری و برنامهها و رتبه 2 234 را در منطقه ماليزيا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 168 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 20 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -169 و در ۲۴ ساعت گذشته برابر 0 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 22.86% 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 3 926 بازدید دریافت میکند. در اولین روز معمولاً 0 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 26 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند framework, object, dataset, tba, depth تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“All the AI with papers. Every day fresh updates about #DeepLearning #MachineLearning #LLM & #ComputerVision
Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/
#AI #chatGPT”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 21 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.
17 168
مشترکین
اطلاعاتی وجود ندارد24 ساعت
-357 روز
-16930 روز
آرشیو پست ها
🤬Music vs. Face Recognition🤬
👉At their recent concerts, Massive Attack turned surveillance into art: crafting a haunting audiovisual show that exposes the dangers of facial recognition tech. Audiences were scanned with mock surveillance, confronting them with the intrusive power of #AI in real time
👉Review https://t.ly/VMrPC
👉News https://t.ly/aj1an
A few “leaks” for you from the #Nvidia presentation I’m right now. Impressive stuff.
Ps: sorry for the shitty pics ♥️
🌀 CLOPS: Vision-Driven Avatar 🌀
👉CLOPS is the first human avatar solely uses egocentric vision to perceive its surroundings and navigate. CLOPS is able to realistically move in a scene and use egocentric vision in order to find a goal by combining a data driven low level motion prior with a Q-Learning policy. A loop of visual perception & motion. Code announced💙
👉Review https://t.ly/RXp64
👉Paper https://arxiv.org/pdf/2509.19259
👉Project markos-diomataris.github.io/projects/clops/
👉Repo TBA
🏆 MOSEv2 Challenge 2025 Winner 🏆
👉A practical solution for complex segmentation based on the Segment Concept (SeC), a concept-driven segmentation framework that shifts from conventional feature matching to the progressive construction and utilization of high-level, object-centric representations. Repo under Apache 2.0💙
👉Review https://t.ly/2MjNm
👉Paper https://arxiv.org/pdf/2509.19183
👉Paper (SeC) https://arxiv.org/pdf/2507.15852
👉Project https://rookiexiong7.github.io/projects/SeC/
👉Repo https://github.com/OpenIXCLab/SeC
🫓 WINNER of LSVOS Challenge 🫓
👉SaSaSa2VA introduces Segmentation Augmentation to improve global video understanding while remaining efficient, and employs Selective Averaging at inference to robustly fuse complementary predictions. This approach achieves SOTA on the 7th LSVOS Challenge (RVOS track). A practical solution with full repo under Apache💙
👉Review https://t.ly/aH4mB
👉Paper https://arxiv.org/pdf/2509.16972
👉Repo https://github.com/magic-research/Sa2VA
🐳 Invariant Saliency Detection 🐳
👉SI-SOD: invariant salient object detection is a paper investigating a fundamental yet underexplored issue in Salient Object Detection (SOD): the size-invariant property for evaluation protocols, particularly in scenarios when multiple salient objects of significantly different sizes appear within a single image. Repo released💙
👉Review https://lnkd.in/p/dZBfbSsf
👉Paper https://arxiv.org/pdf/2509.15573
👉Project https://ferry-li.github.io/SI_SOD/
👉Repo https://github.com/Ferry-Li/SI-SOD
🔥🔥 It's time to decide whether you want to give LinkedIn your data for AI training or not 🔥🔥
Set here: http://linkedin.com/mypreferences/d/settings/data-for-ai-improvement
👽DAM for SAM2 Tracking👽
👉From the University of Ljubljana a novel distractor-aware drop-in memory module for SAM2. Reducing the tracking drift toward distractors and improves redetection capability after object occlusions. DAM4SAM outperforms SAM2.1, SOTA on 10 benchmarks. Repo released 💙
👉Review https://t.ly/8aR59
👉Paper https://arxiv.org/pdf/2509.13864
👉Project jovanavidenovic.github.io/dam-4-sam/
👉Repo github.com/jovanavidenovic/DAM4SAM
I’m keeping the channel free from users’ interactions to avoid SPAM. The only way to interact is commenting in the subchannels after being accepted. Do you like this setting?
I’m keeping the channel free from interaction to avoid SPAM. The only way to interact is commenting the post after being accepted in the subchannel. Do you like this setting?
🍕 Superpixel Anything (SOTA) 🍕
👉 SuperPixel Anything Model, a versatile framework for segmenting images. Extracting image features for superpixel generation blended with a large-scale pretrained model for semantic-agnostic segmentation to ensure superpixels alignement with masks. Damn romantic. Repo & Dataset available💙
👉Review https://t.ly/rpxRh
👉Paper arxiv.org/pdf/2509.12791
👉Repo github.com/waldo-j/spam
🛡️3D Prompted Vision-LLM🛡️
👉#Nvidia unveils SR-3D a novel aware vision-language model that connects single-view 2D images and multi-view 3D data through a shared visual token space. Flexible region prompting, allowing users to annotate regions with bounding boxes, segmentation masks on any frame, or directly in 3D, without the need for exhaustive multi-frame labeling. Code & Dataset announced💙
👉Review https://t.ly/5Y2c5
👉Paper https://arxiv.org/pdf/2509.13317
👉Project https://www.anjiecheng.me/sr3d
👉Repo TBA
🔥🔥 How We Use ChatGPT 🔥🔥
👉By July 2025, ChatGPT has 700M+ users sending more than 2.5B+ messages per day. About 29,000 messages per second. This paper documents eight important facts about ChatGPT usage in the last three years. 63 pages of impressive statistics. To read.💙
👉Review https://t.ly/QYHSi
🦠🦠 Segment & Track Any Cell 🦠
👉RWTH unveils a novel zero-shot cell tracking framework by integrating Segment Anything 2 (SAM2) into the tracking pipeline. Source Code released💙
👉Review https://t.ly/n_srg
👉Paper https://arxiv.org/pdf/2509.09943
👉Repo https://github.com/zhuchen96/sam4celltracking
