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:
Mostrar más📈 Análisis del canal de Telegram Artificial Intelligence && Deep Learning
El canal Artificial Intelligence && Deep Learning (@deeplearning_ai) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 57 527 suscriptores, ocupando la posición 2 234 en la categoría Tecnologías y Aplicaciones y el puesto 5 894 en la región India.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 57 527 suscriptores.
Según los últimos datos del 03 septiembre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -235, y en las últimas 24 horas de 2, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 0%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 0 visualizaciones. En el primer día suele acumular 0 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
- Intereses temáticos: El contenido se centra en temas clave como github, learning, estimation, dataset, engineer.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“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:”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 04 septiembre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
57 527
Suscriptores
+224 horas
-537 días
-23530 días
Archivo de publicaciones
Repost from Machine Learning with Python
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Pippo: High-Resolution Multi-View Humans from a Single Image
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🚀 3DGazeNet: Revolutionizing Gaze Estimation with Weak-Supervision! 🌟
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🌟 Discover 6DRepNet: The Ultimate Head Pose Estimation Model!
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Watch the performance showcase on GitHub for future advancements.
[Source Code] [Paper]
join our community:
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⚽ FIFA World Cup 3D Human Pose Dataset ⚽
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✅ Calibrated moving cameras & accurate trajectories
📄 Paper: arxiv.org/pdf/2501.02771
📊 Dataset: Access here
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🔥 Shanghai AI Lab Introduces RTMW: Real-Time Multi-Person Whole-Body Pose Estimation 🔥
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• Open Source: Code and pre-trained models available
🔗 Discover More:
* Source code: Github
* Paper: Read the paper
✅ https://t.me/deeplearning_ai
🔥 Shanghai AI Lab Introduces RTMW: Real-Time Multi-Person Whole-Body Pose Estimation 🔥
• Blazing Speed: 940+ FPS on GPU, 50–300+ FPS on CPU
• High-Performance Models: Supports 2D/3D whole-body pose estimation
• Cutting-Edge Architecture: Built upon RTMPose with FPN & HEM
• Wide Dataset Coverage: Manually aligned keypoints across 14 open datasets
• Extensive Framework Support: ONNX, TensorRT, ncnn, and OpenVINO
• Open Source: Code and pre-trained models available
🔗 Discover More:
* Source code: Github
* Paper: Read the paper
✅ https://t.me/deeplearning_ai
OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving
🔗 Discover More:
* Source code: Github
* Paper: Read the paper
✅ https://t.me/deeplearning_ai
