GIS&IT Story

“Self-driving Research in Review: CVPR 2019 Digest” by Lyft Level 5 https://link.medium.com/8N8m6VIiL1

“Kepler.GL & Jupyter Notebooks: Geospatial Data Visualization with Uber’s opensource Kepler.GL” by Abdishakur https://link.medium.com/3MkAuWSFC1

테이블 목록 조회 SELECT RELNAME AS TABLE_NAME FROM PG_STAT_USER_TABLES 컬럼 목록 조회 SELECT * FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_CATALOG = '데이터베이스명' AND TABLE_NAME = '테이블명' ORDER BY ORDINAL_POSITION; 기본키 조회 SELECT CC.COLUMN_NAME AS COLUMN_NAME FROM INFORMATION_SCHEMA.TABLE_CONSTRAINTS TC ,INFORMATION_SCHEMA.CONSTRAINT_COLUMN_USAGE CC WHERE TC.TABLE_CATALOG = '데이터베이스명' AND TC.TABLE_NAME = '테이블명' AND..

“Create location-based stories with minimal code” by Mapbox https://link.medium.com/h9xOZ6z5n1

로드뷰 촬영시 저가의 라이다로 촬영 동시에 뎁스맵 생성 시설의 위치를 정확히 예측하여 시설물과 같은 곳에서 좀 더 현장감있게 활용 가능 http://m.elec4.co.kr/article/articleView.asp?idx=24016&fbclid=IwAR27akrti0aBOujgIcz_OZ4gnbeyj3Ck0jFftvZFvG_kvcPsTKCTmHbkMQc 자율주행 위해 시작한 공간정보, 스마트시티에 먼저 적용합니다 자율주행 위해 시작한 공간정보, 스마트시티에 먼저 적용합니다 2019-09-06 전동엽 기자, imdy@elec4.co.kr 인터뷰 스트리스(Stryx) 박일석 대표 영상과 센서 정보 결합해, 측정 즉시 사용가능한 데이터 생성 스트리스(Stryx)는 흔히 ‘스트리트뷰’라고 불리는 파노라마 이미..

“Filling in the gaps: How Mapillary uses PyTorch to improve maps everywhere and for everyone” by PyTorch https://link.medium.com/RFhuq7J330

“Loading Data from OpenStreetMap with Python and the Overpass API” by Nikolai Janakiev https://link.medium.com/GkRdGhEOO0

“Using Image Segmentation to identify Rooftops in low-resolution Satellite images” by Rudradeb Mitra https://link.medium.com/RxrzDnCMO0

“Introducing kepler.gl for Jupyter” by Shan He https://link.medium.com/hIsyKXxYj0

“How Lyft Creates Hyper-Accurate Maps from Open-Source Maps and Real-Time Data” by Albert Yuen https://link.medium.com/YpGug6vR4Z