AlexNet, a groundbreaking neural network developed in 2012 by Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton, has been released in source code form by the Computer History Museum in collaboration with Google. This model significantly advanced the field of AI by demonstrating a massive leap in image recognition capabilities.
The ESP32-S3 AI Camera is a high-performance intelligent camera module designed for efficient video processing, edge AI, and voice interaction. Features include edge image recognition, night vision, and wireless connectivity.
The article discusses the ability of AI systems to interpret images, particularly focusing on the limits and reliability of these systems in answering questions about visual content. The author, Dan Russell, challenges readers to evaluate how well AI can identify objects in provided images and what kinds of questions can be reliably answered by AI.
Qwen2.5-VL, the latest vision-language model from Qwen, showcases enhanced image recognition, agentic behavior, video comprehension, document parsing, and more. It outperforms previous models in various benchmarks and tasks, offering improved efficiency and performance.
This project demonstrates how to use the ESP32-CAM to capture an image of a vehicle's license plate, send it to a cloud server for recognition, and display the recognized number plate on an OLED screen. The project includes setup instructions, code, and component details.
