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Doug Fenstermacher

Doug Fenstermacher's personal website

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Latest posts

Epochron Multi-Stopwatch

Most stopwatches assume one runner and one clock. Epochron is built for coaches and timers tracking multiple people at once. It supports group stopwatches for relays, heats, or ranked comparisons, and get live split predictions mid-race instead of doing the math yourself. It runs entirely in the browser, works offline (built for track meets with no signal), and keeps all data on your device. No…

XDoG: Computing Aesthetically Pleasing Lines

A deeper dive into modern approaches for generating aesthetically pleasing lines based on difference-of-Gaussians (DoG) edge detections.

Streamline Hatching: A Programmer’s Attempt at Computational Drawing

Sharing an attempt at computational hatching. Using structure tensors, edge tangent flow, and streamline integration to transform photographs into hand-drawn-looking illustrations.

Balancing LLM Prompt Analytics and User Privacy

Learn how to implement effective prompt analytics for large language models while safeguarding user privacy. Discover key strategies, best practices, and ethical considerations in this guide.

Neural Variational Document Models with PyTorch for Topic Extraction

Discover how Neural Variational Document Models, implemented using PyTorch, improve topic modeling and unsupervised learning in natural language processing. Learn about the architecture, training process, and applications of these latent variable models for text analysis and beyond.

Harnessing X-Means Clustering and CIE2000 for Visually Striking Dominant Color Extraction

Discover how to harness the power of the X-Means clustering algorithm and CIE2000 color distance metric to accurately extract dominant colors from images. This advanced technique combines unsupervised machine learning with human color perception principles to generate visually appealing and representative color palettes. Perfect for data-driven design, image analysis, and computer vision…

Boosting Web Performance: Implementing K-Means Clustering with WebAssembly and Emscripten

Exploring complexities of optimizing web performance by implementing K-Means clustering algorithms using WebAssembly and Emscripten.

2 Trustworthy Alternatives to Improving Performance Lists in Track & Field

Improving meet performance lists in track & field using the previous performances of the competitors

FitnessJS

A Typescript library for physical fitness calculations

Data Simplification & Summarization

Simplifying polylines and trajectories using the Ramer-Douglas-Puecker algorithm, and summarizing graphs/networks to speed up computations using grouping-based and compression-based algorithms.