首页> 外文OA文献 >Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation
【2h】

Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation

机译:深度珊瑚礁,深度学习:将深度网络移向实时图像注释

摘要

The mismatch between human capacity and the acquisition of Big Data such as Earth imagery undermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. Artificial intelligence (AI) solutions to Big Data issues are urgently needed as these could prove to be faster, more accurate, and cheaper. Reducing costs of managing protected areas in remote deep waters and in the High Seas is of great importance, and this is a realm where autonomous technology will be transformative.
机译:人的能力与获取大数据(例如地球图像)之间的不匹配破坏了对《生物多样性公约》(CBD)和爱知目标的承诺。迫切需要针对大数据问题的人工智能(AI)解决方案,因为这些解决方案被证明可以更快,更准确,更便宜。降低管理偏远深水区和公海保护区的成本非常重要,这是自主技术将变革的领域。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号