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
"Neural Turing Machine" in Tensorflow

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[CVPR 2022] PoseTriplet: Co-evolving 3D Human Pose Estimation, Imitation, and Hallucination under Self-supervision (Oral)

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meProp: Sparsified Back Propagation for Accelerated Deep Learning (ICML 2017)

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[ICLR 2021] "CPT: Efficient Deep Neural Network Training via Cyclic Precision" by Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin

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Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.

YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-

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Deep Markov Factor Analysis (NeurIPS2021)

Deep Markov Factor Analysis (DMFA) Codes and experiments for deep Markov factor analysis (DMFA) model accepted for publication at NeurIPS2021: A. Farn

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A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases,

Chris Hughes 110 Dec 23, 2022
A CV toolkit for my papers.

PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to

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Differential rendering based motion capture blender project.

TraceArmature Summary TraceArmature is currently a set of python scripts that allow for high fidelity motion capture through the use of AI pose estima

William Rodriguez 4 May 27, 2022
Code corresponding to The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents

The Introspective Agent: Interdependence of Strategy, Physiology, and Sensing for Embodied Agents This is the code corresponding to The Introspective

0 Jan 10, 2022
PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmentation

Self-Supervised Anomaly Segmentation Intorduction This is a PyToch implementation of A Novel Self-supervised Learning Task Designed for Anomaly Segmen

WuFan 2 Jan 27, 2022
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks

Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp

Friederike Metz 7 Apr 23, 2022
Object classification with basic computer vision techniques

naive-image-classification Object classification with basic computer vision techniques. Final assignment for the computer vision course I took at univ

2 Jul 01, 2022
This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting.

GAN Memory for Lifelong learning This is a pytorch implementation of the NeurIPS paper GAN Memory with No Forgetting. Please consider citing our paper

Miaoyun Zhao 43 Dec 27, 2022
Prml - Repository of notes, code and notebooks in Python for the book Pattern Recognition and Machine Learning by Christopher Bishop

Pattern Recognition and Machine Learning (PRML) This project contains Jupyter notebooks of many the algorithms presented in Christopher Bishop's Patte

Gerardo Durán-Martín 1k Jan 07, 2023
DilatedNet in Keras for image segmentation

Keras implementation of DilatedNet for semantic segmentation A native Keras implementation of semantic segmentation according to Multi-Scale Context A

303 Mar 15, 2022
Conversion between units used in magnetism

convmag Conversion between various units used in magnetism The conversions between base units available are: T - G : 1e4

0 Jul 15, 2021
Learning with Subset Stacking

Learning with Subset Stacking (LESS) LESS is a new supervised learning algorithm that is based on training many local estimators on subsets of a given

S. Ilker Birbil 19 Oct 04, 2022
Re-TACRED: Addressing Shortcomings of the TACRED Dataset

Re-TACRED Re-TACRED: Addressing Shortcomings of the TACRED Dataset

George Stoica 40 Dec 10, 2022