Fine-tuning PaliGemma for Custom Object Detection
Step-by-step guide to fine-tune PaliGemma for custom object detection, covering setup, dataset preparation, training, evaluation, and deployment. Includes practical tips and important considerations.
Teeth Detection Using YOLOv8 and Python
Learn to detect and label teeth using YOLOv8 and Python. Master dataset preparation, model training, and making predictions with bounding boxes in this hands-on tutorial.
Vehicle Tracking and Speed Estimation Using Computer Vision - Open Source Tutorial
Learn to track vehicles and estimate their speed using computer vision techniques. Covers object detection, multi-object tracking, perspective transformation, and speed estimation with practical code implementation.
YOLOv9 Tutorial - Train Model on Custom Dataset
Learn to set up, train, and deploy YOLOv9 for custom object detection, including model evaluation, inference, and practical applications like self-service checkout systems.
Getting Started with Google Coral Dev Board Micro - Low-Power Object Detection
Learn to train and deploy a custom object detection model on the Google Coral Dev Board Micro, achieving fast inference speeds with low power consumption. Hands-on guide covers data collection, model training, and deployment.
Flood Detection with YOLO V8 Segmentation - One-Class Image Segmentation
Learn to detect floods using Yolo V8 image segmentation. Covers dataset preparation, model training, and testing on new images to generate segmentation masks highlighting flooded areas.
Dog Segmentation with YOLOv8 for Images and Videos
Learn to segment dogs in images and videos using YOLOv8 and Python. Train AI, isolate dogs from backgrounds, and merge with custom scenes. Step-by-step guide with code included.
Dwell Time Analysis with Computer Vision - Real-Time Stream Processing
Optimize processes using computer vision for wait time analysis. Learn object detection, tracking, and time calculation in zones to enhance customer experience and improve efficiency.
Object Detection Using Detection Transformer (DETR) for Bone Fracture Dataset
Learn to build an advanced object detection system using DETR, covering data preparation, model implementation, training, and inference with PyTorch, Transformers, and PyTorch Lightning.
DenseNet Deep Neural Network Architecture Explained
Comprehensive explanation of DenseNet architecture, including its benefits and implementation in PyTorch. Covers theory, results, and practical coding walkthrough for deep learning enthusiasts.
Object Detection with Faster R-CNN in C# Using ONNX on CPU
Implement object detection using Faster R-CNN in C# with ONNX format on CPU, leveraging machine learning for efficient image analysis.
Localization vs. Semantics: Visual Representations in Unimodal and Multimodal Models
Explore visual representations in unimodal and multimodal models, comparing their strengths in label prediction and dense prediction tasks. Gain insights into language's role in visual learning.
Unlocking the Power of ML for Your JavaScript Applications with TensorFlow.js
Explore TensorFlow.js for ML in JavaScript: learn to integrate, retrain models, and leverage ML beyond browsers. Includes demos of virtual makeup try-on and radiology diagnostics.
Beyond Sentiment Analysis - Real Time Object Detection with ML NET
Explore real-time object detection using ML.NET, learn about computer vision applications, and discover tools for image labeling and model building in the .NET ecosystem.
Perception Deception - Physical Adversarial Attack Challenges
Explore physical adversarial attacks on object detection systems, focusing on YOLOv3. Learn tactics to overcome challenges in real-world scenarios and understand implications for AI security.
Hacking Object Detectors Is Just Like Training Neural Networks
Explore techniques for deceiving object detectors by comparing the attack process to neural network training. Learn how applying training techniques can improve adversarial attacks on state-of-the-art systems.
RECL - Responsive Resource-Efficient Continuous Learning for Video Analytics
Innovative video analytics framework integrating model reuse and online retraining for efficient, adaptive DNN models. Optimizes GPU allocation and leverages shared model zoo for improved performance across diverse vision tasks.
Firebase ML Kit - Machine Learning Made Easy
Explore Firebase ML Kit's APIs for Android development, including face detection, text recognition, and object detection. Learn to implement these features in your apps without deep ML knowledge.
ObjectSeeker - Certifiably Robust Object Detection against Patch Hiding Attacks via Patch-agnostic Masking
Explore a novel approach to robust object detection that counters patch hiding attacks using patch-agnostic masking, enhancing security in computer vision applications.
Hiding Objects from Computer Vision by Exploiting Correlation Biases
Exploiting correlation biases in computer vision systems to create adversarial images that hide objects from detection, using examples like dogs and frisbees vs. stop signs and pizza.
My Google Glass Sees Your Passwords
Innovative computer vision attack automatically recognizes touch screen inputs from a distance, posing significant security risks. Countermeasures include a context-aware privacy-enhancing keyboard for sensitive information.