clint-kristopher-morris Goto Github PK

anomaly-detection-by-deep-learning-wavelet-transform

big-data-quality-cross-check

Improving Traffic Data Quality by Cross-Checking Loop-Based Data with Video Detection Data

context-informed-multi-seq-2-single-seq

VDS stations are more densely deployed for monitoring traffic and providing real-time information. By matching VDS stations to CCS sites, a deep learning model called Contextual Informed Multi-Sequence to Single-Sequence (CIMS2SS) is created to generate or estimate CCS data from VDS data.

dino_concise

enabling-risk-aware-routing

Enabling Risk-Aware Routing: Harnessing Feature-Rich Big Data for High-Resolution Crash Risk Modeling Using Tree Ensemble

gdot-rp20-07

RP 20-07: Improving Traffic Data Quality by Cross-Checking Loop-Based Data with Video Detection Data

improving-crash-classification-modeling-with-resampling-methods

Improving Crash Classification Modeling with Resampling Methods

multi-vehicle-collision-patterns-on-freeways

perceiver-transformer

reliable-transposition-of-labeled-images

Enhancing Classifier Training with Advanced Image Augmentation Techniques

romberg-integration-visualization

Romberg Integration: Visualization

sequential-connected-component-labeling-c-and-python

synthetic-parallel-selenium

To maximize data acquisition, the speed of selenium scraping can be significantly improved by employing a synthetic multi-threaded approach

tutorials

Miscellaneous Tutorials

wells-fargo-anomaly-detection-competition

yolo-assisted-image-scrape

Utilizing self-supervised targeted image scraping techniques can enhance sparse and imbalanced datasets, to improved performance of classification algorithms.