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Latest Object Detection AI Videos

Find the latest for Object Detection technology videos

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... 1:9:48
Python + AI: Vision models

Microsoft Reactor

1+ months ago 1K views

Multimodal LLMs, which can process both images and text simultaneously, are significantly enhancing AI applications. Specifically, today's presentation focused on how these models analyze visual data, exemplified through image classification and embedding visual and textual data into a unified format. Practical demonstrations illustrated using public URLs and data URIs for image transmission to models. The session also covered practical use cases, including tree loss analysis via charts and insurance fraud detection using images of vehicle damage, emphasizing the benefits and considerations involved in deploying AI for efficient decision-making. Future developments and challenges in multimodal approaches were hinted at through discussions of embeddings and RAG methodologies.
18:21 - 19:09

Showcased using AI for assessing the legitimacy of insurance claims.

Image Recognition Education
... 10:33
SmolDocling OCR: The Best Open Source AI Model for OCR 🚀

AI Anytime

1+ months ago 2K views

Small Doling is an ultra-compact open-source vision language model designed for document understanding and OCR tasks. It boasts 256 million parameters and outperforms existing models like M in optical character recognition. The model provides efficient processing capabilities for various document types and can handle tables, equations, and other structures. Demonstrated through an app, users can convert images to text, markdown, and other formats quickly. Future improvements include enhanced chart recognition and multi-page inference. The accessible codebase supports broader experimentation and implementation in document processing tasks.
03:16 - 03:43

Overview of Small Doling OCR app functionalities for document processing.

Image Recognition Education
... 9:15
Install SmolDocling-256M Locally: Docling-Based AI Model

Fahd Mirza

1+ months ago 1K views

Dockling is introduced as a powerful tool for document processing that simplifies the extraction of data from diverse formats, including images and PDFs. The newly installed multimodal model retains key features of Dockling, such as efficient tokenization and advanced OCR capabilities. It can process mathematical expressions, extract chart data, and preserve document structure, making it versatile for numerous tasks. The video details the installation process, including working within a virtual environment and testing the model's performance with various document types and languages, highlighting its capabilities and limitations in multilingual contexts.
01:48 - 01:56

Installation process for the Dockling model on an Ubuntu system.

Natural Language Processing (NLP) Research & Innovations
... 54:36
Open-source AI models are surpassing closed source (fast) | AI/ML Monthly

Daniel Bourke

1+ months ago 1K views

The video covers recent developments in AI, including a tutorial on bounding box formats for object detection, a custom object detection model using Hugging Face Transformers, and applications in embedded machine learning. It demonstrates the Trashify app, encouraging local cleanup by detecting trash and bins. New tools, such as a memory calculator for ML models and the SaaS offering for segmenting food in images with text input, are highlighted. The speaker emphasizes updates in open-source AI resources, highlighting companies like Google and advancements in model performance.
03:34 - 04:13

New AI applications for image segmentation in real-time using text prompts.

Machine Learning AI Trends
... 13:46
olmOCR-7B - Amazing AI Model for OCR - Image/PDF/Table to Text Recognition

Aleksandar Haber PhD

1+ months ago 1K views

This tutorial demonstrates how to install and run the M OCR model for optical character recognition locally. It introduces Alen AI Institute, known for impactful AI research, and highlights the capabilities of the M OCR model, which recognizes both printed and handwritten text in scanned documents. The tutorial will extensively cover the installation process using Anaconda, ensuring that necessary libraries and Python virtual environments are correctly set up. Users will also learn how to utilize the model with local PDF documents to convert text and save the output efficiently.
03:11 - 03:48

Tutorial on installation steps for using M OCR on a local setup.

Allen Institute for AI Image Recognition Research & Innovations
... 7:27
Computer Vision in Medicine: Revolutionizing Healthcare Through AI

AI & Health | IA & Santé

1+ months ago 1K views

Computer vision is revolutionizing medicine through early disease detection, enhanced surgical precision, and improved hospital hygiene. AI-powered algorithms allow for accurate diagnosis of conditions like cancer and diabetic retinopathy by analyzing medical imaging. The technology plays a significant role in robotic surgery, providing surgeons with augmented reality overlays for better precision. Computer vision assists in monitoring hospital hygiene and tracking chronic diseases, enabling real-time insights that elevate patient care. Ethical considerations, such as data privacy and AI bias, are essential for establishing trust and effective integration into healthcare practices.
03:07 - 03:22

AI-driven systems monitor hospital hygiene compliance, enhancing infection control.

Image Recognition Healthcare
... 38:55
Two Raspberry Pi AI Cameras

DroneBot Workshop

1+ months ago 6K views

The workshop explores artificial intelligence cameras specifically designed for use with Raspberry Pi, comparing the Raspberry Pi AI camera to the Arducam PinSight AI camera. The session covers the setup, functionalities, and software requirements for both cameras, highlighting their capabilities in computer vision, machine learning, and image processing. Key distinctions include how AI processing occurs directly in the camera, freeing up Raspberry Pi resources, and the specific applications these cameras can serve, such as object detection and pose analysis. Practical demonstrations illustrate how to utilize these cameras effectively, providing insights for AI camera projects.
06:39 - 06:46

Sony IMX 500 sensor enables simultaneous video and AI processing.

Raspberry Pi Image Recognition Tech & Hardware
... 15:1
TensorFlow for Beginners - Lesson 2 | AI That Reads Handwriting! (MNIST Neural Network)

The Digital Tutor

1+ months ago 1K views

Teaching computers to recognize handwritten numbers enhances AI skills significantly. This lesson builds on previous learnings where AI was trained to recognize number patterns. Computers perceive images as numerical grids, differentiating brightness levels, which is vital for recognizing patterns. Neural networks, inspired by human brain functionality, learn through analyzing thousands of examples. The lesson details the process of importing datasets from TensorFlow, preparing data for neural networks, scaling pixel values to enhance training efficiency, and defining a model to train and predict handwritten digit recognition, culminating in showcasing the AI's capabilities.
07:05 - 07:30

Demonstrates the impact of scaling pixel values on training efficiency.

Google Neural Network Architectures Education
... 15:1
TensorFlow for Beginners - Lesson 2 | AI That Reads Handwriting! (MNIST Neural Network)

The Digital Tutor

1+ months ago 1K views

Teaching computers to recognize handwritten numbers enhances AI skills significantly. This lesson builds on previous learnings where AI was trained to recognize number patterns. Computers perceive images as numerical grids, differentiating brightness levels, which is vital for recognizing patterns. Neural networks, inspired by human brain functionality, learn through analyzing thousands of examples. The lesson details the process of importing datasets from TensorFlow, preparing data for neural networks, scaling pixel values to enhance training efficiency, and defining a model to train and predict handwritten digit recognition, culminating in showcasing the AI's capabilities.
07:05 - 07:30

Demonstrates the impact of scaling pixel values on training efficiency.

Google Neural Network Architectures Education