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计算机视觉
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== 核心任务 == === 图像分类 === 判断一张图像整体所属的类别,是计算机视觉中最基础的任务。经典数据集如 ImageNet 极大推动了该方向的发展。 === 目标检测 === 在图像中定位并识别出多个物体,输出每个物体的类别与位置(边界框)。代表性方法包括 R-CNN 系列、YOLO 系列等。 === 图像分割 === 将图像划分为若干具有语义意义的区域,可细分为语义分割、实例分割与全景分割,广泛应用于医学影像与自动驾驶。 === 目标跟踪 === 在视频序列中持续定位特定目标,是视频分析与监控的关键技术。 === 三维视觉 === 从二维图像中恢复三维结构,包括立体视觉、深度估计、三维重建与点云处理等。
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