机译:超越对象建议:随机作物合并用于多标签图像识别
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China;
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China;
School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China;
School of Computer Science, Nanjing University of Science and Technology, Nanjing, China;
Department of Electrical and Computer Engineering, National University of Singapore, Singapore;
Image recognition; Proposals; Training; Agriculture; Feature extraction; Standards; Neural networks;
机译:具有多降低区域提案网络的锚盒的RGB-D图像对象检测和多池
机译:基于对象的作物分类使用多时间点-5图像和带有随机林类分类器的纹理特征
机译:结合基于对象的图像分析和随机森林,利用GF-1 / WFV数据进行季节作物映射
机译:具有多缩小区域提议网络和多池的彩色和深度图像目标检测
机译:用于多标签图像识别的图网络
机译:基于内容的焦平面选择和关于全光图像序列上目标跟踪的建议
机译:基于金字塔池模块的多尺度U形卷积自动编码器,用于合成孔径雷达图像中的物体识别