Popular GitHub Repositories for Location

kaldi-asr/kaldi is the official location of the Kaldi project.

A PyTorch implementation of Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis

A modern, web-based photo management server. Run it on your home server and it will let you find the right photo from your collection on any device. Smart filtering is made possible by object recognition, face recognition, location awareness, color analysis and other ML algorithms.

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)

Intelligent job recommendation platform using Java + MySQL + Redis. Supports location-based search, AI keyword extraction, and personalized suggestions.

ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction

Confidence and Byt5 - based geotagging model predicting coordinates from text alone.

Location-Sensitive Visual Recognition with Cross-IOU Loss

Code for the paper "Location-aware Single Image Reflection Removal"

Developed an AI-based system to control the mouse cursor using Python and OpenCV with the real-time camera. Fingertip location is mapped to RGB images to control the mouse cursor.

Use the Intel D435 real-sensing camera to realize target detection based on the Yolov3 framework under the Opencv DNN framework, and realize the 3D positioning of the Objection according to the depth information. Real-time display of the coordinates in the camera coordinate system.ADD--Using Yolov5 By TensorRT model,AGX-Xavier,RealTime Object Detection

This repository has been moved. The new location is in https://github.com/TexasInstruments/edgeai-tensorlab

LVCNet: Efficient Condition-Dependent Modeling Network for Waveform Generation

Using Transformer protein embeddings with a linear attention mechanism to make SOTA de-novo predictions for the subcellular location of proteins :microscope:

Connect all CCTV cameras to this system to track someone's live location in a premise using facial recognition. It can be also used to maintain records of people entering a premise using their face instead of bio-metrics/cards/manual Entry

The official code and datasets for "Zero-Shot Multi-View Indoor Localization via Graph Location Networks" (ACMMM 2020)

Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics

Code for the paper: Adversarial Training Against Location-Optimized Adversarial Patches. ECCV-W 2020.

Thanks to the proliferation of smart devices, such as smartphones and wearables, which are equipped with computation, communication and sensing capabilities, a plethora of new location-based services and applications are available for the users at any time and everywhere. Understanding human mobility has gain importance to offer better services able to provide valuable products to the user whenever it's required. The ability to predict when and where individuals will go next allows enabling smart recommendation systems or a better organization of resources such as public transport vehicles or taxis. Network providers can predict future activities of individuals and groups to optimize network handovers, while transport systems can provide more vehicles or lines where required, reducing waiting time and discomfort to their clients. The re

Adding the Feature "Real World Path Direction" by tapping on Map. GoogleMap will give us the direction to that location from user location then click on "ARView" & you will get the real-world path direction. Also added "Reachability" for finding path in Google map. -- Also added .mlmodel for car-detection. Initially trained the model using Convolutional Neural Network in TensorFlow, then convert the .h5 output into .mlmodel. Use it in the application. please check : https://github.com/ashislaha/CarDetection-Keras & https://github.com/ashislaha/CarDetection-iOS for more details how to train a model. -- In ARFrame generates capturedImage which is the input to .mlmodel for detecting that car is present in the image or not. -- This project combines both ARKit & CoreML.