Master's Thesis on Simultaneous Localization and Mapping in dynamic environments. Separately reconstructs both the static environment and the dynamic objects from it, such as cars.

Density-aware Single Image De-raining using a Multi-stream Dense Network (CVPR 2018)

The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.

[ACCV22] Structure Representation Network and Uncertainty Feedback Learning for Dense Non-Uniform Fog Removal, https://arxiv.org/abs/2210.03061

Efficient matrix representations for working with tabular data

Implementation of Artificial Neural Networks using NumPy

A QT tool used to annotate temporal segments of a video with events which each have unique and customisable information.

Upsampling method for an input cloud using mls method of PCL

Intrusion Detection System - IDS example using Dense, Conv1d and Lstm layers in Keras / TensorFlow

Hand Gesture Recognition using CNNs and Perceptrons in realtime (OpenCV)

Continuation of the original pimd-dense from 1998-1999, gaps filled with frog DNA from pimd

CP-APR Tensor Decomposition with PyTorch backend. pyCP_APR can perform non-negative Poisson Tensor Factorization on GPU, and includes an interface for anomaly detection using the extracted latent patterns.

A subpixel dense refinement U-NET like architecture for Vessel Segmentation from Retinal fundas images

layers

Cholesterol is calculated from the given set of data.

PIM-DM multicast routing protocol implementation (RFC3973)

Free WordPress Plugin: This volume calculator uses a density formula ρ = m/V to find densities of different substances and objects. It calculates the third one for two given values - density, mass, or volume of a substance. www.calculator.io/density-calculator/

Implementation of a multicast routing protocol named HPIM-DM (dissertation work)

Cross-platform mobile Neural network C library for training and inference on the device. CPU only. It fits for time-series data.

A Fast, Extensible Trainer and Extensions for Pytorch