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.

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

[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.

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

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

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.

PIM-DM multicast routing protocol implementation (RFC3973)

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

A Fast, Extensible Trainer and Extensions for Pytorch

colbert for dense retrieval, including multi view version, dureader-retrieval as an example

Keras implementation of Mixed-scale Dense Net (MS-D Net) object segmentation

A simple code for creating your own custom layer in TensorFlow using Keras API. Here I have created the Dense layer same as the regular dense layer available in the Keras API.

人工智能大作业-Fashion数据集 分类

Building Convolution Neural Networks from Scratch

RiskMaster is an intelligent platform for individual investors to assess cryptocurrency market risks. It combines historical trend analysis and predictive neural networks - LSTM

This Project is based on Neural Network to classify between Dogs and Cats.