针对分选线上樱桃叠果和表面瑕疵难以准确实时分割的问题,该研究提出了一种基于改进YOLOv8n-seg的多分支实时分割模型,命名SemIns-YOLOv8。该模型在YOLOv8n-seg的PAN-FPN(path aggregation network for feature pyramid network)模块后...针对分选线上樱桃叠果和表面瑕疵难以准确实时分割的问题,该研究提出了一种基于改进YOLOv8n-seg的多分支实时分割模型,命名SemIns-YOLOv8。该模型在YOLOv8n-seg的PAN-FPN(path aggregation network for feature pyramid network)模块后引入基于上下文集成的语义分割模块,并采用交叉熵损失与Dice Loss联合的损失函数,替代原始实例分割模块对果梗和瑕疵进行识别,既提升了尺寸较小及特征不明显瑕疵的识别精度,又缩短了图像的识别时间。同时,通过提高特征图分辨率并引入豪斯多夫距离损失(Hausdorff distance loss,HD Loss)构建边界特征增强的实例分割模块,实现了樱桃重叠果体的精准分离。试验结果表明,SemIns-YOLOv8在樱桃分割任务中果体mAP50-95(mean average precision at intersection over union thresholds from 0.50 to 0.95)、果梗IoU和瑕疵mIoU(mean intersection over union)分别为98.20%、92.15%和65.97%,与YOLOv8n-seg相比,提升了2.10、2.33和14.35个百分点,并且在模型输入尺寸为1024×384像素时,单帧推理时间为23 ms,可为线上水果外观品质实时分选提供参考。展开更多
The hydrological character parameters of the litter amount, the maximum water capacity and water absorption speed of the litter on the forest land under four type of \%Abies fabri\% forest (young, half_mature,mature a...The hydrological character parameters of the litter amount, the maximum water capacity and water absorption speed of the litter on the forest land under four type of \%Abies fabri\% forest (young, half_mature,mature and overmature stand)on the Gongga Mountain were studied in this paper. The result showed that the litter amount under the overmature stand was the maximum(67 8?t·hm -2 ), the second was the mature stand(53 4 t·hm -2 ), the third was the half mature stand(40 4 t·hm -2 ), the fourth was the young stand(32 6?t·hm -2 ). The maximum water capacity of the undecomposed litter under the mature stand was 428 8% of the litter’s dry weight, that of the litter under the overmature stand was 411 6%, that of the litter under the half_mature stand was 378 8%, that of the litter under the young stand was 296 7%. The maximum water capacity of the half_decomposed litter under the mature stand was 234 5% of the litter’s dry weight, that of the litter under the overmature stand was 175 6%, that of the litter under the half mature stand was 160 3%, that of the litter under the young stand was 132 5%. The equation between the water absorption speed of the litter and the soaked time is S=kt n. The result also shows that the litter’s variation with the time has no relation to forest age, while its decomposition degree is positively related to stand age.展开更多
文摘为探究不同植物生长调节剂对杜鹃叶片生长和花期的影响,以长圆团叶杜鹃(Rhododendron orbiculare)为研究对象,在施用9种植物生长调节剂后的30 d和60 d,采用野外调查法测量叶片的长度、宽度等生长指标,使用英国皇家园艺学会比色卡(royal horticultural society color chart,RHSCC)和色差仪对叶片颜色指标进行测量,定期定点观察初花期。结果表明:胺新脂(DA-7)、复硝酚钠、吲哚丁酸钾、十三烷醇、四甲基戊二酸和6-苄氨基嘌呤(6-BA)可有效扩大成熟叶面积,且所有处理均能显著促进新梢伸长;在施用植物生长调节剂后,成熟叶片的RHSCC值和明度(L^(*))、红绿轴指数(a^(*))、黄蓝轴指数(b^(*))数值整体由偏黄向绿色转变。复硝酚钠综合效果最为突出,在第30天和第60天时的叶片生长速度均最快;在第60天时,成熟叶片长度和宽度分别较对照提高20.4%和19.6%,新梢长度增长125%;复硝酚钠处理组的成熟叶片RHSCC为NN137B,叶色描述为灰橄榄绿,L^(*)为37.07,b^(*)为15.06,为所有试验组中最低,绿色最深,其叶绿素含量最高;此外复硝酚钠表现出最强的促花性,初花期提前达10 d。复硝酚钠兼具叶片快速促生、显著增绿与调控初花期的多重优势,最适宜作为长圆团叶杜鹃叶面生长调节剂。
文摘针对分选线上樱桃叠果和表面瑕疵难以准确实时分割的问题,该研究提出了一种基于改进YOLOv8n-seg的多分支实时分割模型,命名SemIns-YOLOv8。该模型在YOLOv8n-seg的PAN-FPN(path aggregation network for feature pyramid network)模块后引入基于上下文集成的语义分割模块,并采用交叉熵损失与Dice Loss联合的损失函数,替代原始实例分割模块对果梗和瑕疵进行识别,既提升了尺寸较小及特征不明显瑕疵的识别精度,又缩短了图像的识别时间。同时,通过提高特征图分辨率并引入豪斯多夫距离损失(Hausdorff distance loss,HD Loss)构建边界特征增强的实例分割模块,实现了樱桃重叠果体的精准分离。试验结果表明,SemIns-YOLOv8在樱桃分割任务中果体mAP50-95(mean average precision at intersection over union thresholds from 0.50 to 0.95)、果梗IoU和瑕疵mIoU(mean intersection over union)分别为98.20%、92.15%和65.97%,与YOLOv8n-seg相比,提升了2.10、2.33和14.35个百分点,并且在模型输入尺寸为1024×384像素时,单帧推理时间为23 ms,可为线上水果外观品质实时分选提供参考。
文摘The hydrological character parameters of the litter amount, the maximum water capacity and water absorption speed of the litter on the forest land under four type of \%Abies fabri\% forest (young, half_mature,mature and overmature stand)on the Gongga Mountain were studied in this paper. The result showed that the litter amount under the overmature stand was the maximum(67 8?t·hm -2 ), the second was the mature stand(53 4 t·hm -2 ), the third was the half mature stand(40 4 t·hm -2 ), the fourth was the young stand(32 6?t·hm -2 ). The maximum water capacity of the undecomposed litter under the mature stand was 428 8% of the litter’s dry weight, that of the litter under the overmature stand was 411 6%, that of the litter under the half_mature stand was 378 8%, that of the litter under the young stand was 296 7%. The maximum water capacity of the half_decomposed litter under the mature stand was 234 5% of the litter’s dry weight, that of the litter under the overmature stand was 175 6%, that of the litter under the half mature stand was 160 3%, that of the litter under the young stand was 132 5%. The equation between the water absorption speed of the litter and the soaked time is S=kt n. The result also shows that the litter’s variation with the time has no relation to forest age, while its decomposition degree is positively related to stand age.
