Official implementation of "Where are the People? A Multi-Stream Convolutional Neural Network for Crowd Counting via Density Map from Complex Images" presented in IWSSIP 2019

Code for "Multi-Stream Networks and Ground-Truth Generation for Crowd Counting" presented in IJECES

Train a CSRNet for estimating a crowd distribution

ResMap, Compute the local resolution of 3D density maps, (support python3 and maps in variant shape)

This repository implements naive density map to visualize high-dimension data.

A collaborative list of awesome CryoEM (Cryo Electron Microscopy) resources.

Estimate number and location of people in crowd image

Density Map in R, OpenstreetMap

LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.

A c# library to generate heightmaps

Repository to preview, describe, and link to Tableau dashboard.

Address the crowd counting problem on the Mall dataset (sparse) by exploring regression-based (Xception) and density-based (CSRNet) approaches.

The "Crime in Vancouver" Dash application provides users with an interactive visualization of crime data in Vancouver, British Columbia. Users can explore geographical and temporal patterns of various types of crimes across different neighborhoods, streets, seasons, and years.

"deep-individual-tracker" is a deep learning-based tracking method that takes into account the overlap of individuals to detect. This repository provides annotation, detection, trackers, and monitoring tools.

This bundle provides ChimeraX command for recognizing ligands in cryoEM and X-ray crystallography maps using deep learning.