Gesture and sign recognition is a growing field in computer vision, powering accessibility tools and natural user interfaces. Most beginner projects rely on hand landmarks or small CNNs, but these often miss the bigger picture because gestures are no...| freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
Our interview series is here to deliver you digestible intelligence from the organizations and innovators leading the world of AI in healthcare - through expert and in-depth interviews.| AI Accelerator Institute
Learn what a VLM is and how to use VLMs in Roboflow Workflows to perform various vision tasks.| Roboflow Blog
Learn how to use Florence-2 in Roboflow Workflows for zero-shot object detection, OCR, and more.| Roboflow Blog
In this post we break down Meta AI's DINOv3 research paper, which introduces a state-of-the-art Computer Vision foundation models family The post DINOv3 Paper Explained: The Computer Vision Foundation Model appeared first on AI Papers Academy.| AI Papers Academy
Dive into Continuous Thought Machines, a novel architecture that strive to push AI closer to how the human brain works The post Continuous Thought Machines (CTMs) – The Era of AI Beyond Transformers? appeared first on AI Papers Academy.| AI Papers Academy
Dive into Perception Language Models by Meta, a family of fully open SOTA vision-language models with detailed visual understanding The post Perception Language Models (PLMs) by Meta – A Fully Open SOTA VLM appeared first on AI Papers Academy.| AI Papers Academy
I let an AI pick out my outfits using computer vision and pictures of social media fashion influencers.| daleonai.com
In this article, we create a background replacement application using BiRefNet. We cover the code using Jupyter Notebook and create a Gradio application as well. The post Background Replacement Using BiRefNet appeared first on DebuggerCafe.| DebuggerCafe
In this article, we explore the BiRefNet model for high-resolution dichotomous segmentation. Along with discussing the key elements of the paper, we also create a small background removal codebase usign the pretrained model. The post Introduction to BiRefNet appeared first on DebuggerCafe.| DebuggerCafe
IBM releases GraniteDocling, an open-source compact document AI model with improved accuracy, multilingual support, and enterprise readiness| MarkTechPost
Posted by Colby Banbury, Emil Njor, Andrea Mattia Garavagno, Vijay Janapa Reddi – Harvard UniversityTinyML is an exciting frontier in machine learning, enabling models to run on extremely low-power devices such as microcontrollers and edge devices. However, the growth of this field has been stifled by a lack of tailored large and high-quality datasets. That's where Wake Vision comes in—a new dataset designed to accelerate research and development in TinyML.| The TensorFlow Blog
Designed for millions of robotic developers, NVIDIA Jetson Thor delivers 2,070 FP4 teraflops to tackle complex applications including agentic AI, high-speed sensor processing and general robotics tasks.| NVIDIA Blog
Learn how to take a dataset from Voxel51 into Roboflow, train an RF-DETR model, and deploy it to the cloud, private servers, or edge devices. This step-by-step guide walks you through dataset conversion, model training, workflow testing, and real-world integration.| Roboflow Blog
With this project, we integrate real-time feedback and computer vision to develop a hand-washing steps-tracking system using a Python application and a Roboflow-trained model.| Roboflow Blog
Explore VL-Cogito’s curriculum RL innovations for multimodal reasoning in AI. Boost chart, math, and science problem-solving accuracy| MarkTechPost
The latest Granite vision model recently came in second on the OCRBench leaderboard, and is the best-performing small model on the chart.| IBM Research
IBM’s new vision-language model for enterprise AI can extract knowledge locked away in tables, charts, and other graphics, bringing enterprises closer to automating a range of document understanding tasks.| IBM Research
LiveXiv is updated monthly, to provide a potentially more accurate look at vision-language model performance| IBM Research
The human visual system adapts to a wide range of lighting conditions, from warm sunlight to the cool glow of office fixtures. Yet, a smartphone camera applies numerous system-level processing steps and enhancements. As a result, the same color sample can appear differently under varying illumination or on different devices. In a professional environment, such inconsistency leads to significant waste of time and resources. In this article, the It-Jim mobile app development team explores how s...| It-Jim
Authors| Chris Choy
Authors| Chris Choy
Authors| Chris Choy
Authors| Chris Choy
Authors| Chris Choy
The Neural Radiance Fields (NeRF) proposed an interesting way to represent a 3D scene using an implicit network for high fidelity volumetric rendering. Compared with traditional methods to generate textured 3D mesh and rendering the final mesh, NeRF provides a fully differntiable way to learn geometry, texture, and material properties for specularity, which is very difficult to capture using non-differentiable traditional reconstruction methods.| Chris Choy
Learn how to use Roboflow Workflows to collect and preprocess image training data for use in building a vision model.| Roboflow Blog
Learn what F1 score is, for what it is used, and how to calculate F1 score.| Roboflow Blog
Learn how computer vision effectively allows HSE teams to augment and strengthen their worksite safety and operations.| viso.ai
Enhance driving safety with Vision AI for real-time alerts on speeding and proximities, preventing accidents and ensuring operational continuity.| viso.ai
NVIDIA was today named an Autonomous Grand Challenge winner at the Computer Vision and Pattern Recognition (CVPR) conference, held this week in Nashville, Tennessee. The announcement was made at the Embodied Intelligence for Autonomous Systems on the Horizon Workshop. This marks the second consecutive year that NVIDIA’s topped the leaderboard in the End-to-End Driving at Read Article| NVIDIA Blog
We launched the first in a new webinar series lifting the lid on how enterprise teams can get started with computer vision.| viso.ai
Computer vision for detecting issue during 3d printing with automatic notification to Discord and Telegram and pausing the print. This plugin has minimal HW requirements. Recommended hardware is Raspberry pi 5, older version are not supported.| OctoPrint Plugin Repository
Today we are releasing RF-DETR, a state-of-the-art real-time object detection model. Learn more about how RF-DETR works and how to use the model.| Roboflow Blog
The 10 Hottest Computer Vision Trends Shaping 2025| Gramener Blog
Carrying out DINOv2 segmentation experiments for fine-tuning and transfer learning and comparing the results.| DebuggerCafe
Learn how to train a ResNet-50 model for image classification.| Roboflow Blog
Learn what OCR data extraction is and what models you can use to programmatically read the contents of images.| Roboflow Blog
Learn about computer vision and how you can use it to solve problems.| Roboflow Blog
Learn about the latest advancements in AI helping automotive manufacturers modernize their factories and improve productivity.| Roboflow Blog
DINOv2 is a self-supervised computer vision model which learns robust visual features that can be used for downstream tasks.| DebuggerCafe
This article explores computer vision trends and how advances in AI technology will impact industry, businesses, and society.| viso.ai
End-to-end tutorial for detecting and counting objects on a conveyor belt using computer vision.| Roboflow Blog
Master Contrastive Learning with SimCLR and BYOL, theoretical foundations, and step-by-step BYOL implementation of learning representations| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
We break down all current You Only Look Once (YOLO) versions from Joseph Redmon's original release to v9, v10, v11, and beyond.| viso.ai
Intro Since many of my posts were mostly critical and arguably somewhat cynical [1], [2], [3], at least over the last 2-3 years, I decided to switch gears a little and let my audience know I'm actually a very constructive, busy building stuff most of the time, while my ranting on the blog is mostly a side project to vent, since above everything I'm allergic to naive hype and nonsense. Nevertheless I've worked in the so called AI/robotics/perception for at least ten years in industry now (an...| Piekniewski's blog
Computer vision plays a big part in deploying automated visual inspection, making it possible to process the amounts of data from this automation.| AI Accelerator Institute
Computer vision in AR and VR uses digital elements for spatial mapping, object recognition, and creating immersive virtual environments.| viso.ai
This article explores the history of self-supervised learning, introduces DINO Self-Supervised Learning, and shows how to fine-tune DINO for road segmentation| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
As computer vision AI continues to advance, it will bring more sophisticated analysis, smarter training routines and deeper fan engagement.| Griffon Webstudios
Ball tracking is crucial for AI systems to analyze sports effectively, but it's challenging due to factors like the ball's small size, high velocity, complex backgrounds, similar-looking objects, and varying lighting. This tutorial will teach you how to overcome these challenges.| Roboflow Blog
With modern advancements in artificial intelligence and computational power, computer vision has become an integral part of everyday life. Computers’ ability to ‘see’ and interpret the world around them helps in the analysis of the massive amounts of data created in daily operations.| AI Accelerator Institute
Le passage à l'électrique est aussi l'occasion pour les constructeurs automobiles d'optimiser et moderniser leurs processus industriels. Dans...-Intelligence artificielle| www.usine-digitale.fr
The ability to track moving objects across multiple camera feeds is of immense value to us. From baggage monitoring in busy airports to product tracking in large retail stores, there is a strong case for applications of this nature. In principle, this is simple. The tracking system first detects objects entering a camera’s view and […] The post Multi-Camera Object Tracking Using Custom Association Model appeared first on QBurst Blog.| QBurst Blog
Explore top Industry 4.0 companies driving digital manufacturing, enhancing efficiency, and optimizing processes. Read this blog.| Gramener Blog
We dive into the world of AI design tools and examine five leading solutions: Canva, Adobe Photoshop, Beautiful.ai, Decktopus, and Midjourney.| TOPBOTS
Florence-2 is a lightweight vision-language model open-sourced by Microsoft under the MIT license.| Roboflow Blog
Learn what OpenCV is, what you can do with OpenCV, how OpenCV performs on various tasks when run on CPU vs. GPU, and more.| Roboflow Blog
See how nine different OCR models compare for scene text recognition across industrial domains.| Roboflow Blog
Learn how to monitor retail queues to identify when customers have been waiting for too long.| Roboflow Blog
Training a robust facial keypoint detection model by fine-tuning the pretrained ResNet50 model with the PyTorch framework,| DebuggerCafe
Learn how to train a YOLOv9 model on a custom dataset.| Roboflow Blog
YOLOv8 object tracking and counting unveils new dimensions in real-time tacking; explore its mastery in our detailed guide, your key to mastering the tech.| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
The YOLO (You Only Look Once) series of models, renowned for its real-time object detection capabilities, owes much of its effectiveness to its specialized loss functions. In this article, we delve into the various YOLO loss function integral to YOLO's evolution, focusing on their implementation in PyTorch. Our aim is to provide a clear, technical| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
Discover moving object detection using OpenCV, blending contour detection with background subtraction for real-time application in security and traffic.| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
My recent experiences with using WebRTC in a mobile application gave me a chance to get familiar with its capabilities and limitations, namely being reliant ...| spieswl.github.io
In this guide, we evaluate Google's Gemini LMM against several computer vision tasks, from OCR to VQA to zero-shot object detection.| Roboflow Blog
Learn how to use computer vision in your data analytics pipelines.| Roboflow Blog
In this guide, we walk through how to deploy computer vision models (i.e. YOLOv8) offline using Roboflow Inference.| Roboflow Blog
In this guide, we share findings experimenting with GPT-4 with Vision, released by OpenAI in September 2023.| Roboflow Blog