Akash rawal
Akash rawal @akash_rawal_1 ·
Meta's SAM 3.1 is here & it's insane! - Segments ANYTHING in images & videos using just text prompts - ~7x faster inference at 128 objects on a single H100 - Object Multiplex = shared memory for joint multi-object tracking Open source @metaai #SAM3 #AI #ComputerVision
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HackerNoon | Learn Any Technology
HackerNoon | Learn Any Technology @hackernoon ·
Explore ultra-lightweight image classifiers using compact CNNs and handcrafted features, achieving strong accuracy with minimal parameters. - by @saptakbhoumik hackernoon.com/building-ultra… #smallneuralnetworks #computervision
Building Ultra-Lightweight Image Classifiers with TinyVision (Part 1) | HackerNoon

Explore ultra-lightweight image classifiers using compact CNNs and handcrafted features, achieving strong accuracy with minimal parameters.

From hackernoon.com
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AIQUEST
AIQUEST @AiquestAcademy ·
Fix blurry photos like a pro. Finally. RealRestorer uses large models to handle nine common degradation types. It beats all existing models on the RealIR-Bench test. Code and project demo page are available. What would you restore with this? #ComputerVision #AI
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Sergio Cuéllar ☁️ (@ 🏠)
Sergio Cuéllar ☁️ (@ 🏠) @5ergio_Cuellar ·
🐟�� #FishMonitoring #ComputerVision Researchers from MIT and Woodwell Climate Research Center develop a computer vision-powered system to automate fish counting during river herring migration. This innovation improves efficiency, data quality, and news.mit.edu/2026/augmentin…Jw
Augmenting citizen science with computer vision for fish monitoring

Monitoring river herring migration is essential for conservation and fisheries management. Researchers have now demonstrated a method using video and computer vision to supplement traditional methods...

From news.mit.edu
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