LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.

Related tags

Deep LearningLocUNet
Overview

LocUNet

LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accurate estimates of the radio maps of each BS, and is tailored to work in realistic propagation environments in urban settings.

See the paper Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach for more information.

The associated dataset RadioLocSeer is available at the project main page.

For reproducibility, see the compute capsule.

Perspective: Julia for Biologists

Perspective: Julia for Biologists 1. Examples Speed: Example 1 - Single cell data and network inference Domain: Single cell data Methodology: Network

Elisabeth Roesch 55 Dec 02, 2022
Largest list of models for Core ML (for iOS 11+)

Since iOS 11, Apple released Core ML framework to help developers integrate machine learning models into applications. The official documentation We'v

Kedan Li 5.6k Jan 08, 2023
A minimal implementation of face-detection models using flask, gunicorn, nginx, docker, and docker-compose

Face-Detection-flask-gunicorn-nginx-docker This is a simple implementation of dockerized face-detection restful-API implemented with flask, Nginx, and

Pooya-Mohammadi 30 Dec 17, 2022
Pytorch implementation of Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization https://arxiv.org/abs/2008.11646

[TCSVT] Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization LPN [Paper] NEWs Prerequisites Python 3.6 GPU Memory = 8G Numpy 1.

46 Dec 14, 2022
Trained on Simulated Data, Tested in the Real World

Trained on Simulated Data, Tested in the Real World

livox 43 Nov 18, 2022
Best practices for segmentation of the corporate network of any company

Best-practice-for-network-segmentation What is this? This project was created to publish the best practices for segmentation of the corporate network

2k Jan 07, 2023
Implementation of ETSformer, state of the art time-series Transformer, in Pytorch

ETSformer - Pytorch Implementation of ETSformer, state of the art time-series Transformer, in Pytorch Install $ pip install etsformer-pytorch Usage im

Phil Wang 121 Dec 30, 2022
Reproduction of Vision Transformer in Tensorflow2. Train from scratch and Finetune.

Vision Transformer(ViT) in Tensorflow2 Tensorflow2 implementation of the Vision Transformer(ViT). This repository is for An image is worth 16x16 words

sungjun lee 42 Dec 27, 2022
Learning 3D Part Assembly from a Single Image

Learning 3D Part Assembly from a Single Image This repository contains a PyTorch implementation of the paper: Learning 3D Part Assembly from A Single

18 Dec 21, 2022
Semi-supervised Domain Adaptation via Minimax Entropy

Semi-supervised Domain Adaptation via Minimax Entropy (ICCV 2019) Install pip install -r requirements.txt The code is written for Pytorch 0.4.0, but s

Vision and Learning Group 243 Jan 09, 2023
the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"

EOW-Softmax This code is for the paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration". Accepted by ICCV21. Usage Commnd exa

Yezhen Wang 36 Dec 02, 2022
A clean and robust Pytorch implementation of PPO on continuous action space.

PPO-Continuous-Pytorch I found the current implementation of PPO on continuous action space is whether somewhat complicated or not stable. And this is

XinJingHao 56 Dec 16, 2022
Speedy Implementation of Instance-based Learning (IBL) agents in Python

A Python library to create single or multi Instance-based Learning (IBL) agents that are built based on Instance Based Learning Theory (IBLT) 1 Instal

0 Nov 18, 2021
An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

An Ensemble of CNN (Python 3.5.1 Tensorflow 1.3 numpy 1.13)

0 May 06, 2022
Hyper-parameter optimization for sklearn

hyperopt-sklearn Hyperopt-sklearn is Hyperopt-based model selection among machine learning algorithms in scikit-learn. See how to use hyperopt-sklearn

1.4k Jan 01, 2023
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)

Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild Akash Sengupta, Ignas Budvytis, Robert

Akash Sengupta 149 Dec 14, 2022
PyTorch implementation for 3D human pose estimation

Towards 3D Human Pose Estimation in the Wild: a Weakly-supervised Approach This repository is the PyTorch implementation for the network presented in:

Xingyi Zhou 579 Dec 22, 2022
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding

Rot-Pro : Modeling Transitivity by Projection in Knowledge Graph Embedding This repository contains the source code for the Rot-Pro model, presented a

Tewi 9 Sep 28, 2022
Crowd-Kit is a powerful Python library that implements commonly-used aggregation methods for crowdsourced annotation and offers the relevant metrics and datasets

Crowd-Kit: Computational Quality Control for Crowdsourcing Documentation Crowd-Kit is a powerful Python library that implements commonly-used aggregat

Toloka 125 Dec 30, 2022
A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation

A Differentiable Recipe for Learning Visual Non-Prehensile Planar Manipulation This repository contains the source code of the paper A Differentiable

Bernardo Aceituno 2 May 05, 2022