2021 Artificial Intelligence Diabetes Datathon

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Deep LearningAIDD2021
Overview

A I D D 2021 최종 포스터

A.I.D.D. 2021

2021 Artificial Intelligence Diabetes Datathon

A.I.D.D. 2021은 ‘2021 인공지능 학습용 데이터 구축사업’을 통해 만들어진 학습용 데이터를 활용하여 당뇨병을 효과적으로 예측할 수 있는가에 대한 AI 모델링 챌린지입니다.

본 대회는 NAVER CLOUD PLATFORM의 고성능 클라우드 인프라 상에서 운영되며 네이버의 클라우드 머신러닝 플랫폼인 NSML(Naver Smart Machine Learning)과 함께 합니다. NAVER CLOUD PLATFORMNSML은 개발자들이 "모델 개발과 알고리즘 최적화"에만 집중할 수 있도록 필요한 제반 환경을 제공합니다. AI 전문가들과 함께 인공지능 모델 개발에 도전하실 분들을 기다리고 있습니다.

챌린지

당뇨병 데이터를 이용하여 당뇨병 발생을 예측하는 인공지능 모델 개발

  1. 예선
  • 당뇨병 발생 예측 인공지능 모델 개발
  1. 본선
  • 당뇨병 발생 예측 인공지능 모델 고도화!

시상 및 혜택

  • 총상금: 추후 공개
구분 시상 상금
대상 (1팀)
경희의료원장상 500만원
최우수상 (1팀)
경희의과학연구원장상 300만원
우수상 (2팀)
인공지능빅데이터팀장상 100만원

대회 일정

행사내용 일정 장소/방식
참가 신청
2021년 10월 22일 ~ 11월 16일 온라인
개회식 및 설명회
2021년 11월 18일 14:00~ 온라인
예선 대회
2021년 11월 19일 ~ 11월 22일 온라인(NSML)
본선 대회
2021년 11월 26일 ~ 11월 29일 온라인(NSML)

심사기준

  • 서면평가: 참가신청서, 참가팀 역량 (예선 진출팀 40개 팀 선발)
  • 예선: NSML 리더보드 상위 점수 순으로 선발 (본선 진출 20개 팀 선발)
  • 본선: 종료 시점 NSML 리더보드 상위 점수 순으로 시상
    *모델 사이즈 제한 300MB
    *동점자 발생 시 모델 제출 시간이 빠른 순서, 모델 크기가 작은 순서 순으로 우선순위 결정

참가신청

  1. 신청 기간: 2021년 10월 22일 ~ 11월 16일
  2. 신청 방법: 온라인

Github 게시판

  • 온라인 게시판 대회기간 중 10:00~19:00 실시간 운영
Source code for "Progressive Transformers for End-to-End Sign Language Production" (ECCV 2020)

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PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference

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This code finds bounding box of a single human mouth.

This code finds bounding box of a single human mouth. In comparison to other face segmentation methods, it is relatively insusceptible to open mouth conditions, e.g., yawning, surgical robots, etc. T

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Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation (ICCV 2021)

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The backbone CSPDarkNet of YOLOX.

YOLOX-Backbone The backbone CSPDarkNet of YOLOX. In this project, you can enjoy: CSPDarkNet-S CSPDarkNet-M CSPDarkNet-L CSPDarkNet-X CSPDarkNet-Tiny C

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Learning Lightweight Low-Light Enhancement Network using Pseudo Well-Exposed Images This repository contains the implementation of the following paper

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Hacktober Fest 2021 🎉 Open source is changing the world – one contribution at a time! 🎉 This repository is made for beginners who are unfamiliar wit

Abhilash M Nair 32 Dec 11, 2022
Ağ tarayıcı.Gönderdiği paketler ile ağa bağlı olan cihazların IP adreslerini gösterir.

NetScanner.py Ağ tarayıcı.Gönderdiği paketler ile ağa bağlı olan cihazların IP adreslerini gösterir. Linux'da Kullanımı: git clone https://github.com/

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Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems

Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems This repository is the official implementation of Rever

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Official code for On Path Integration of Grid Cells: Group Representation and Isotropic Scaling (NeurIPS 2021)

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Ruiqi Gao 39 Nov 10, 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks

This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required

Felix Biggs 0 Feb 04, 2022
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"

Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe

YueSong 32 Dec 25, 2022
pytorch implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network arXiv:1609.04802

PyTorch SRResNet Implementation of Paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"(https://arxiv.org/abs

Jiu XU 436 Jan 09, 2023
Active Offline Policy Selection With Python

Active Offline Policy Selection This is supporting example code for NeurIPS 2021 paper Active Offline Policy Selection by Ksenia Konyushkova*, Yutian

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