1.MSA R-CNN Multi-scale Aggregation R-CNN MSA RCNN:该网络将关键点定位和人体目标检测整合到一个网络中。该网络的主要创新点为:MS-RoIAlign和MS-KpsNet。网络整体框架如下图所示。 Multi-scale RoIAlign Block MS-RoIAlign:从多个不同尺度的特征图中获取人体框特征,并聚合。 原始的RoIAlign从单一的特征图...
MSA R-CNN achieved an mAP of 74.37% on the DIOR dataset when the gamma value was set to 0.2 and 81.97% on the DOTA dataset when the gamma value was set to 0.1 with the same learning rate, outperforming state-of-the-art models on both datasets. The proposed system demonstrates ...
1、MSA测量系统分析的案例分析从选矿生产过程中选取10个铁精矿样品,选用3名化检验人员,使用同一套检验系统,按 不同的顺序分别检测10个样品,重复3遍。检测结果数据如下表。铁莆聲样品中TFf的翡定结果DetenninationDetennination TrullsTrulls ofof totaltotal ironiron ioio ironiron cnncentwtecnncentwte samples...
相较于传统的文本情感分析,它不再仅仅局限于词汇、短语及其语义关系的解析,而是融入了面部表情的微妙变化、语调的抑扬顿挫等更多维度的信息,使得情感描述更为生动,情感传达也更为精准且丰富。 与此同时,随着现代社会生活节奏的加快和工作压力的增大,抑郁症已成为职场中不可忽视的心理问题。早期发现并干预抑郁症,对于防...
卷积层是CNNs的基本构建模块。设 X \in R^{n_{w} \times n_{e} \times c_{i n}} 和W^{k} \in R^{k \times k \times c_{i n} \times c_{\text {out }} \text { 为输入 }} 特征, 卷积的为kernel-size为 \mathrm{k}, 其中 n_{w} 、 n_{e} 、 c_{i n} 和c_{\text ...
TLC5970、FUF1MTRTB、H9CCNNN8GTML、APTD1608LZGCK、V6-1212D2、TPS7A7001DDAR、HKQ04025N1H-T、ECW05-0303SH、HL7018、BAV100WL、TAS5611A、MT3012ASBR、UA709AHMQB、TPS62130RGT、BTN8984、GAL16V8D7LJ、SMSJ120CTR-13、IH4812S、MSA2111、BL24C64A-CS-R、WDD20-15S2、VG-2412D2、E1Z24A5-5、...
(1) Densely Connected CNN withMulti-scaleFeatureAttentionforText Classification Addattention...NetworkforFine-Grained Image Recognition (4) LEARN TO PAYATTENTION(5) Weighted Channel Dropoutfor 2019 AAAI Transferable Attention for Domain Adaptation
Wei, Y.; Wang, Z.; Xu, M.: Road structure refined cnn for road extraction in aerial image. IEEE Geosci. Remote Sens. Lett. 14(5), 709–713 (2017) Article Google Scholar Li, J.; Liu, Y.; Zhang, Y.; Zhang, Y.: Cascaded attention denseunet (cadunet) for road extraction from...
To verify the detection performance of our proposed MSA-YOLOv5 algorithm, we compared it with other ten algorithms, including YOLOv3, YOLOv4, Scaled_YOLOv4, YOLOv5s, TPH-YOLOv5, YOLOR, YOLOv7, SSD, Mask R–CNN, and Faster R–CNN. The results are shown in Table 1. MSA-YOLOv5 achieve...
𝑋𝑊𝑒𝑎𝑡ℎ𝑒𝑟=CNN(𝑋𝑊𝑒𝑎𝑡ℎ𝑒𝑟)XWeather=CNN(XWeather) (22) As shown in Equation (18), after the training, the generated new sample is extracted as the weather feature 𝑋𝑂𝑢𝑡𝑝𝑢𝑡𝐷𝑒𝑐𝑜𝑑𝑒𝑟XDecoderOutput, and, as shown in...