Embedding Custom Meta-Data (Bounding Boxes) into HLS Video Streams Introduction This article explores techniques for embedding custom meta-data, specifically bounding boxes, into HLS video streams. Bounding boxes can provide valuable…
Classify or Keyword Match a Natural Language String or Phrase Classifying or Keyword Matching a Natural Language String or Phrase Introduction Classifying or keyword matching a natural language string or…
Parameter Selection in AdaBoost Parameter Selection in AdaBoost AdaBoost, short for Adaptive Boosting, is a powerful ensemble learning algorithm widely used in classification tasks. Its effectiveness lies in its ability…
Building a Convolutional Neural Network in Azure Machine Learning Building a Convolutional Neural Network in Azure Machine Learning Convolutional Neural Networks (CNNs) are a powerful type of neural network particularly…
Python Deployment Package with SKLEARN, PANDAS, and NUMPY Issues Python Deployment Package with SKLEARN, PANDAS, and NUMPY Issues Deploying machine learning models built with libraries like scikit-learn (SKLEARN), Pandas, and…
R – mice – machine learning: re-use imputation scheme from train to test set Introduction Imputation is a crucial step in handling missing data, especially when preparing datasets for machine…
Apple Vision: Struggling to Recognize Single Numbers as Regions The Issue Apple’s Vision framework, a powerful tool for image analysis, is facing a challenge with recognizing individual numbers within a…
Load Balancing and Scheduling Algorithms Load Balancing and Scheduling Algorithms Load balancing and scheduling algorithms are essential for efficient resource allocation and performance optimization in distributed systems. They aim to…
Event Correlation and Filtering: How to, Where to Start? Event Correlation and Filtering: How to, Where to Start? In the modern world of complex systems and data deluge, understanding patterns…
Mean Shift Implementation in C++ Mean Shift Implementation in C++ Introduction The mean shift algorithm is a non-parametric clustering technique used to identify dense regions in data. It operates by…
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