deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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Yeonseok Kim PRO
yeonseok-zeticai
AI & ML interests
On device AI with mobile hardware utilizations
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liked
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8 days ago
deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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4 months ago
👋 We're excited to share our project on mobile face detection using MediaPipe and ZETIC.MLange.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
reacted
to
their
post
with 😎
4 months ago
👋 We're excited to share our project on mobile face detection using MediaPipe and ZETIC.MLange.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
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yeonseok-zeticai's activity
liked
a
model
8 days ago
reacted to
their
post with 👍😎🤗🧠❤️👀🚀🔥
4 months ago
Post
1136
👋 We're excited to share our project on mobile face detection using MediaPipe and ZETIC.MLange.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
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update
4 months ago
Post
1136
👋 We're excited to share our project on mobile face detection using MediaPipe and ZETIC.MLange.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
🔑 Key highlights:
1. Introduction to Mediapipe face detection model
2. Developing on-device AI applications with ZETIC.MLange
3. Guide to creating object detection apps utilizing Mobile NPUs
📱 Learn how to build a high-performance face detection app that operates entirely on-device, no cloud required! We explore:
- Real-time face analysis techniques
- Enhanced security measures
- Privacy protection strategies
🎥 Check out our demo video showcasing real-time face detection:
Face detection Demo: https://youtu.be/GXtJKk7MdjQ?si=41UFKL8IBwx5nlxs
📚 Full Tutorial
For a step-by-step guide and in-depth discussion, read our full blog post:
https://zetic.ai/blog/implementing-face-detection-on-device-ai-with-zetic-mlange
We'd love to hear your thoughts, experiences, or questions in the comments below.
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🚀 Revolutionary Method to Convert YOLOv8 to On-Device AI with mobile NPU utilizations
Attention AI developers and engineers!
Discover how ZETIC.MLange can effortlessly transform YOLOv8 models into on-device AI with mobile NPU utilizations. 🎉
💡 We highlight the power of mobile NPU, showing how it outperforms CPU in processing speed. The results speak for themselves—NPU-driven execution is faster, smarter, and more efficient.
* Real-time demos are no easy feat but with ZETIC.MLange, we’ve made it possible!
🎥 Watch the video to see how we’re revolutionizing on-device AI.
: https://youtu.be/LkP3JDTcVN8?si=6Ha5vHA-G7jZE9oq
🌟 Our team has successfully implemented YOLOv8 as on-device AI using ZETIC.MLange. This innovative approach enables high-performance object detection across various manufacturers mobile devices.
🔍 Curious about the details? We've shared a comprehensive guide on our blog. Check it out through the link below!
📚 Blog link: https://zetic.ai/blog/implementing-yolov8-on-device-ai-with-zetic-mlange
Attention AI developers and engineers!
Discover how ZETIC.MLange can effortlessly transform YOLOv8 models into on-device AI with mobile NPU utilizations. 🎉
💡 We highlight the power of mobile NPU, showing how it outperforms CPU in processing speed. The results speak for themselves—NPU-driven execution is faster, smarter, and more efficient.
* Real-time demos are no easy feat but with ZETIC.MLange, we’ve made it possible!
🎥 Watch the video to see how we’re revolutionizing on-device AI.
: https://youtu.be/LkP3JDTcVN8?si=6Ha5vHA-G7jZE9oq
🌟 Our team has successfully implemented YOLOv8 as on-device AI using ZETIC.MLange. This innovative approach enables high-performance object detection across various manufacturers mobile devices.
🔍 Curious about the details? We've shared a comprehensive guide on our blog. Check it out through the link below!
📚 Blog link: https://zetic.ai/blog/implementing-yolov8-on-device-ai-with-zetic-mlange