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相关概念视频

Gene Therapy00:59

Gene Therapy

Gene therapy is a technique where a gene is inserted into a person’s cells to prevent or treat a serious disease. The added gene may be a healthy version of the gene that is mutated in the patient, or it could be a different gene that inactivates or compensates for the patient’s disease-causing gene. For example, in patients with severe combined immunodeficiency (SCID) due to a mutation in the gene for the enzyme adenosine deaminase, a functioning version of the gene can be inserted. The...

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BiSeNeXt:基于复杂场景中的改进的BiSeNetV2的叶和疾病细分方法

Bibo Lu1, Yanjun Lu1, Di Liang1

  • 1School of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China.

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这项研究引入了BiSeNeXt用于叶病细分,在复杂的环境中实现了高精度. 这种方法有效地划分了叶子和病斑,改善了作物产量分析.

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美国美国通过 PointRefine疾病斑点细分亚姆叶片的细分

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科学领域:

  • 农业科学
  • 计算机视觉
  • 植物病理学

背景情况:

  • 叶病对的质量和产量产生重大影响,因此需要进行精确的监测.
  • 目前对叶病细分的研究是有限的, 面临着重叠的叶子,不均的照明和不规则的疾病斑点等挑战.
  • 准确的细分对于在种植中识别和管理疾病至关重要.

研究的目的:

  • 开发用于叶病细分的第一个数据集.
  • 提出一个增强的细分方法,BiSeNeXt,在复杂的环境中提高准确性.
  • 提供分析叶健康和疾病的坚实基础.

主要方法:

  • 介绍了第一个叶病细分数据集.
  • 开发了基于BiSeNetV2的增强细分方法BiSeNeXt.
  • 集成的动态特征提取块 (DFEB) 与动态接收场卷积 (DRFConv) 和像素混合 (PixelShuffle) 进行精确的边缘检测.
  • 使用高效非对称多尺度注意力 (EAMA) 来解决病变粘附.
  • 使用PointRefine解码器进行细分预测的自适应性改进.

主要成果:

  • 在叶片细分上实现了97.04%的交界度 (IoU),在疾病细分上实现了84.75%的 IoU.
  • 与DeepLabV3+相比,叶片细分的IOU提高了2. 22%,疾病细分的IOU提高了5. 58%.
  • 与DeepLabV3+相比,显著降低计算成本,只需要11.81%的FLOP和7.81%的参数.

结论:

  • 在复杂的场景中精确而高效地划分叶斑.
  • 拟议的方法为山羊病的分析和管理提供了重大进展.
  • 这项工作为进一步的农业图像分析研究奠定了坚实的基础.