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Wayha Sokxay Technology
- Vientiane, Laos
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21:15
(UTC +07:00) - saypadith
Highlights
- Pro
Stars
An AI based QR code reader that can effectively recognise all kinds of shaped QR codes, coloured QR codes and rotating QR codes.
Stable Diffusion web UI
Opensource IDE For Exploring and Testing Api's (lightweight alternative to postman/insomnia)
This repos contains notebooks for the Advanced Solutions Lab: ML Immersion
List of all training course at SCK and Shi Ha Ri company
A fully functional social media app built with flutter with multiple features
In this video we will learn how to Integrate NodeJS Login and Register API in our Flutter application using JWT Token Authentication.
Create a static markdown blog with less than 5 minutes in deno
A sample cache logic based on hasura trigger
A boilerplate to setup up a flutter app with hasura for graphQL APIs and firebase for user management and providing custom JWTs for authorization.
A boilerplate project created in flutter using MobX and Provider.
Learning to create Machine Learning Algorithms
Connect your Flutter/Dart apps to Hasura simply.
Reference Authentication Flow with Flutter & Firebase
Dev Emotion Tracker With GraphQL powered by Hasura
This version extend from cudaminer which is the fastest Litecoin miner for NVIDIA GPUs. I customize code to run cuda on maximum GPU performance
A repo looking at autoencoders that can be applied to extremely large 2D and 3D tensors.
Python optical flow visualization following Baker et al. (ICCV 2007) as used by the MPI-Sintel challenge
An official implementation of "Learning Memory-guided Normality for Anomaly Detection" (CVPR 2020) in PyTorch.
Papers for Video Anomaly Detection, released codes collection, Performance Comparision.
This repository is for Weakly Supervised Video Anomaly Detection via Center-Guided Discriminative Learning(ICME 2020). The original paper can be found (https://ieeexplore.ieee.org/document/9102722)…
unofficial implementation of paper Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder (MemAE) for Unsupervised Anomaly Detection
Anomaly Detection in Video Sequence with Appearance-Motion Correspondence
Reference models and tools for Cloud TPUs.