一同加入！只要您願意睜大眼。
透過您的雙眼，協助我們訓練AI偵測雨林砍伐。
如果我們不夠嚴謹，我們的生態系統將歷經一段日益惡化的退化過程。起初看似小而微不足道，將隨著時間的流逝而日趨嚴重。 Albert Van Jaarsveld CEO International Institute for Applied Systems Analysis
執行方法
透過人類擴增AI
AI不是憑空產生的。它仰賴人類的專業知識作為其訓練數據的基礎。您輸入的資訊給了AI模型學習的範例。愈多的範例，愈能提升其模型精準度。
模型週期概述
Image Collection
Satellite images are continuously collected for areas affected by deforestation.
Image Classification
Through crowdsourcing, thousands of people like you sort and label the images that show signs of deforestation.
Machine Learning
Models are trained to recognize areas of deforestation based on this labeled data, learning and improving at every iteration.
Evaluation
Models are tested for accuracy. High-quality models are deployed, and lower quality models continue to reiterate.
Deployment
Even deployed models continue to be evaluated for accuracy. The best model is run constantly to alert experts when new areas of deforestation are detected so immediate action can be taken.
使用技術
幕後的大工程
隨著電腦視覺模型每日分析上百萬張圖像來辨識新的雨林砍伐跡象，政府決策者和援助組織得以搶先介入，守護這些雨林。
為守護地球，讓議題持續發燒。
我們的知識與熱誠對保護世界資源能有實質的影響。快呼同引伴一起來#雨林 (#rainforest)參與。