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pascalmusabyimana
pascal-maker
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https://pascal-maker.github.io/developedbypascalmusabyimana/
PascalMusabyim1
pascal-maker
pascal-musabyimana-573b66178
AI & ML interests
computer vision, nlp , machine learning and deeplearning
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With https://huggingface.co/Robonine team we recently verified the rotational speed of the Feetech STS3250 servo motor (12 V, 50 kg·cm torque, magnetic encoder) to compare measured performance with the official specification. According to the datasheet: - Rated speed: 0.133 s per 60° Calculation: - 0.133 s × 6 = 0.798 s per full rotation - 1 / 0.798 = 1.253 revolutions per second - 1.253 × 60 = 75.2 RPM This confirms the official specification of approximately 75 RPM at 12 V under no load. Our measurement: - Encoder output: 5,300 values per second - Encoder resolution: 4,096 counts per revolution Calculation: - Revolutions per second = 5,300 ÷ 4,096 = 1.294 rev/s - RPM = 1.294 × 60 = 77.6 RPM Result: The measured value differs by only about 2–3% from the datasheet specification, confirming that the STS3250 performs very close to its rated no-load speed. This close agreement validates both the servo’s performance and our measurement approach. Video: https://youtube.com/shorts/_O_mVZvYQlQ?feature=share #servo #robotics #automation #motioncontrol #mechatronics #Feetech #STS3250 #engineering #datasheet #precision #hardwaretesting #roboticsengineering
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🚀💡🌟 New Research Alert - ICCV 2025 (Oral)! 🌟🪄🚀 📄 Title: LoftUp: Learning a Coordinate-based Feature Upsampler for Vision Foundation Models 🔝 📝 Description: LoftUp is a coordinate-based transformer that upscales the low-resolution features of VFMs (e.g. DINOv2 and CLIP) using cross-attention and self-distilled pseudo-ground truth (pseudo-GT) from SAM. 👥 Authors: Haiwen Huang, Anpei Chen, Volodymyr Havrylov, Andreas Geiger, and Dan Zhang 📅 Conference: ICCV, 19 – 23 Oct, 2025 | Honolulu, Hawai'i, USA 🇺🇸 📄 Paper: https://huggingface.co/papers/2504.14032 🌐 Github Page: https://andrehuang.github.io/loftup-site 📁 Repository: https://github.com/andrehuang/loftup 🚀 ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers 🚀 Added to the Foundation Models and Representation Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/foundation-models-and-representation-learning.md 📚 More Papers: more cutting-edge research presented at other conferences in the https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin 🔍 Keywords: #LoftUp #VisionFoundationModels #FeatureUpsampling #Cross-AttentionTransformer #CoordinateBasedLearning #SelfDistillation #PseudoGroundTruth #RepresentationLearning #AI #ICCV2025 #ResearchHighlight
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🚀🏷️🌟 New Research Alert - ICCV 2025 (Oral)! 🌟🧩🚀 📄 Title: Heavy Labels Out! Dataset Distillation with Label Space Lightening 🔝 📝 Description: The HeLlO framework is a new corpus distillation method that removes the need for large soft labels. It uses a lightweight, online image-to-label projector based on CLIP. This projector has been adapted using LoRA-style, parameter-efficient tuning. It has also been initialized with text embeddings. 👥 Authors: @roseannelexie, @Huage001, Zigeng Chen, Jingwen Ye, and Xinchao Wang 📅 Conference: ICCV, 19 – 23 Oct, 2025 | Honolulu, Hawai'i, USA 🇺🇸 📄 Paper: https://huggingface.co/papers/2408.08201 📺 Video: https://www.youtube.com/watch?v=kAyK_3wskgA 🚀 ICCV-2023-25-Papers: https://github.com/DmitryRyumin/ICCV-2023-25-Papers 🚀 Added to the Efficient Learning Section: https://github.com/DmitryRyumin/ICCV-2023-25-Papers/blob/main/sections/2025/main/efficient-learning.md 📚 More Papers: more cutting-edge research presented at other conferences in the https://huggingface.co/spaces/DmitryRyumin/NewEraAI-Papers curated by @DmitryRyumin 🔍 Keywords: #DatasetDistillation #LabelCompression #CLIP #LoRA #EfficientAI #FoundationModels #AI #ICCV2025 #ResearchHighlight
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