深層学習に基づく物体検出アルゴリズム
令和7年2月26日|p.45
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### 2.2.2.1 R-CNN系列算法
R-CNN（Regions with CNN features）是第一个将卷积神经网络应用于目标检测的算法。它首先生成一系列候选区域，然后对每个候选区域提取特征并进行分类和边界框回归。后续的Fast R-CNN、Faster R-CNN等算法在此基础上进行了改进，提高了检测速度和精度。
### 2.2.2.2 YOLO和SSD算法
YOLO（You Only Look Once）和SSD（Single Shot MultiBox Detector）是基于回归的目标检测算法的代表。它们将目标检测问题转化为一个单一的回归问题，直接从输入图像中预测出目标的类别和位置。这类算法具有速度快、实时性好的优点，但精度相对较低。
The Impact of Climate Change on Global Biodiversity
Introduction
Climate change is one of the most pressing environmental issues facing our planet today. Its effects are far-reaching and multifaceted, impacting ecosystems worldwide. One of the most significant consequences of climate change is its profound impact on global biodiversity.
Rising Temperatures and Habitat Loss
As temperatures rise due to increased greenhouse gas emissions, many species struggle to adapt quickly enough to survive in their changing environments. This leads to habitat loss as traditional habitats become unsuitable for certain flora and fauna.
Disruption of Ecosystem Services