Rocco Magnotta’s Post

Event computation means performing calculations and making decisions directly on events as they happen, instead of waiting to store them as data. DADA X agents compute in real-time on the event stream, making decisions and acting as events unfold. It's proactive, not reactive. Check out our latest video to learn more about the power of event computation. It's what will move us from the Information Age to the Era of Causal Control. #AI #Autonomous

Event computation is as transformative as the leap from analog to digital or manual to automated—it's the foundation of the next era of intelligent systems. It enables making decisions directly on events as they happen, instead of waiting to store them as data. DADA X computes in real-time on the event stream, making decisions and acting as events unfold. It's proactive, not reactive. Check out the video to learn more! #Autonomous #EventComputation https://lnkd.in/eG4TPDVi

Unveiling YOLO v10 - The cutting-edge in real-time object detection! Higher accuracy, improved latency, and better object localization. Perfect for AI applications. Learn more in the blog below. #YOLOv10 #ObjectDetection #AI #MachineLearning

Taking on Traffic Light Detection with YOLOv9! I just started exploring YOLOv9, the new object detection powerhouse, and I'm diving straight in with custom traffic light detection! This cutting-edge system boasts: Programmable Gradient Information (PGI): Fights data loss, a deep network nemesis, for reliable training and top-notch performance. Generalized Efficient Layer Aggregation Network (GELAN): This lightweight architecture unlocks PGI's potential, achieving impressive results. YOLOv9 has more accuracy and efficiency, than the previous models without even having massive pre-training datasets. Here is the Link of the Research Paper: https://lnkd.in/dzn8A9-M #AI #ObjectDetection #ComputerVision

 🚀 Excited to kick off my series of blog posts on LinkedIn! Starting with YOLO v1, we'll unravel the intricacies of different YOLO versions and explore the world of object detection from scratch. Join me on this journey through the evolution of computer vision! #ComputerVision #DeepLearning #YOLO #ObjectDetection #MachineLearning #AI

🌊 Exciting Machine Learning Competition: Detect Ocean Internal Waves! 🛰️ Are you ready to dive into the world of Machine Learning and ocean dynamics? AIR Centre - Atlantic International Research Centre is thrilled to announce our latest ML challenge on image classification of internal waves Goal: Develop an algorithm to automatically classifies an image as having or not internal wave(s) in simplified satellite images 🎯 Challenge: Image classification using Sentinel-1 (Copernicus Constellation) data 🔍 Why participate? • Contribute to cutting-edge oceanographic research • Showcase your ML skills on real-world data • Network with experts in remote sensing and ocean science • Potential for your work to impact climate and ocean studies Whether you're a seasoned ML pro or an enthusiastic newcomer, this competition offers a unique opportunity to apply your skills to a fascinating environmental challenge. Ready to make waves? Join us and help unlock the secrets of the ocean from space! 🚀 Note these are simplified images can shall be treated as photographs, so no remote sensing knowledge required. #MachineLearning #SatelliteImagery #OceanScience #DataScience #AICompetition I have created a couple models (Multi-Layer Perceptron (MLP) classifier and a Convolutional Neural Network (CNN)) to validate the dataset and files, and to get a baseline, which you can find here: https://lnkd.in/dHTGkypg

🚀 Excited to share my latest work on real-time person detection and skeleton tracking! Using YOLOv5 and OpenCV, I developed a framework that detects and tracks people in video streams while identifying potential skeletal structures within each detection. This system efficiently counts and monitors individuals in real time by combining deep learning and contour-based image processing. Such technology holds significant promise for applications in crowd management, surveillance, and posture analysis. I’m looking forward to exploring enhanced tracking and skeletal analysis with optimized models, opening the door to expanded applications in various industries. #AI #MachineLearning #ComputerVision #RealTimeTracking #YOLOv5 Bayes Labs

In my latest blog post, I dive deep into t-SNE: 🌐 What is t-SNE 🧠 How the algorithm works 🎯 When to use t-SNE over other dimensionality reduction techniques 📈 Advantages and Disadvantages #DataScience #MachineLearning #DataVisualization #tSNE #BigData #AI

A very interesting development , 3D visualization of model activations using tSNE and cubic spline interpolation summary: 3D Visualization:Utilizes tSNE for dimensionality reduction. tSNE converts high-dimensional model activations to a 3D space. Model Activations:Examines internal layer outputs of neural networks. Helps understand how models process inputs.tSNE (t-Distributed Stochastic Neighbor Embedding) Reduces data dimensionality while preserving local structures. Effective for visualizing high-dimensional data in lower dimensions. Cubic Spline Interpolation:Smoothly connects points in the reduced 3D space. Enhances visualization by interpolating between data points. #3DVisualization #tSNE #ModelActivations #CubicSpline #DataScience #NeuralNetworks #DimensionalityReduction https://lnkd.in/dgXwnZmC