A Activity diagram used in UML 6/9 and SysML B Bachman diagram Booch used in software engineering Block diagram Block Definition Diagram BDD used in SysML C Carroll diagram Cartogram Catalytic cycle Chemical equation Curly arrow diagram Category theory diagrams Cause-and-effect diagram Chord diagram Circuit diagram Class diagram from UML 1/9 Collaboration diagram from UML 2.0 Communication diagram from UML 2.0 Commutative diagram Comparison diagram Component diagram from UML 3/9 Composite structure diagram from UML 2.0 Concept map Constellation diagram Context diagram Control flow diagram Contour diagram Cordier diagram Cross functional flowchart D Data model diagram Data flow diagram Data structure diagram Dendrogram Dependency diagram Deployment diagram from UML 9/9 Dot and cross diagram Double bubble map used in education Drakon-chart E Entity-Relationship diagram ERD Event-driven process chain Euler diagram Eye diagram a diagram of a received telecommunications signal Express-G Extended Functional Flow Block Diagram EFFBD F Family tree Feynman diagram Flow chart Flow process chart Flow diagram Fusion diagram Free body diagram G Gantt chart shows the timing of tasks or activities used in project management Grotrian diagram Goodman diagram shows the fatigue data example: for a wind turbine blades H Hasse diagram HIPO diagram I Internal Block Diagram IBD used in SysML IDEF0 IDEF1 entity relations Interaction overview diagram from UML Ishikawa diagram J Jackson diagram K Karnaugh map Kinematic diagram L Ladder diagram Line of balance Link grammar diagram M Martin ERD Message Sequence Chart Mind map used for learning, brainstorming, memory, visual thinking and problem solving Minkowski spacetime diagram Molecular orbital diagram N N2 Nassi Shneiderman diagram or structogram a representation for structured programming Nomogram Network diagram O Object diagram from UML 2/9 Organigram Onion diagram also known as "stacked Venn diagram" P Package diagram from UML 4/9 and SysML Parametric diagram from SysML PERT Petri net shows the structure of a distributed system as a directed bipartite graph with annotations Phylogenetic tree - represents a phylogeny evolutionary relationships among groups of organisms Piping and instrumentation diagram P&ID Phase diagram used to present solid/liquid/gas information Plant Diagram Pressure volume diagram used to analyse engines Pourbaix diagram Process flow diagram or PFD used in chemical engineering Program structure diagram R Radar chart Radial Diagram Requirement Diagram Used in SysML Rich Picture R-diagram Routing diagram S Sankey diagram represents material, energy or cost flows with quantity proportional arrows in a process network. Sentence diagram represents the grammatical structure of a natural language sentence. Sequence diagram from UML 8/9 and SysML SDL/GR diagram Specification and Description Language. SDL is a formal language used in computer science. Smith chart Spider chart Spray diagram SSADM Structured Systems Analysis and Design Methodology used in software engineering Star chart/Celestial sphere State diagram are used for state machines in software engineering from UML 7/9 Swim lane Syntax diagram used in software engineering to represent a context-free grammar Systems Biology Graphical Notation a graphical notation used in diagrams of biochemical and cellular processes studied in Systems biology System context diagram System structure Systematic layout planning T Timing Diagram: Digital Timing Diagram Timing Diagram: UML 2.0 TQM Diagram Treemap U UML diagram Unified Modeling Language used in software engineering Use case diagram from UML 5/9 and SysML V Value Stream Mapping Venn diagram Voronoi diagram W Warnier-Orr Williot diagram Y Yourdon-Coad see Edward Yourdon, used in software engineering
Soft NMS：传统的NMS是直接抑制掉重叠框中候选框中分数较低的框，而Soft NMS通过修改分数的方式，将重叠的框的分数逐渐降低。 例如，重叠的框的分数会随着IoU值的增加而逐渐减少，而不是直接变为0。 这样做可以让模型更加关注可靠的检测结果，避免错判。
nms有没有问题呢？ 1 首先所有框是按分类置信度得分排序，分类置信度是分类分支的结果和定位的分支是两个不同的网络，分类置信度高的检测框不一定就是最准确的框置。 2 如果两个物体靠的比较近，他们的iou会比阈值高，这样会导致误过滤。 针对这个问题有几个改进想法，如cvpr2017的soft nms ...
对于 one to many label assignment NMS 能否提升 DETR 系列模型，在 Group DETR 论文中就已经给出了回答（如下图）：相比于 DETR 系列使用的 one to one assignment，在 12 epoch training setting 下涨幅相当可观。
研究者进一步比较了Traditional NMS和DIoU NMS的性能，在YOLOv3和SSD上，选取NMS阈值为 [0.43,0.48]。 可以看到DIoU NMS在每个阈值上都优于Traditional NMS，此外还值得一提的是，即便是性能最差的DIoU NMS也比性能最好的Traditional NMS相当或更优，说明即便不仔细调整NMS阈值，DIoU ...
阅读了论文之后对DETR不需要NMS这个特点比较懵懂，有没有大佬可以解释一下为什么DETR不需要NMS也能学习到…
非极大值抑制，简称NMS，还是比较耗时间的。因为是一个迭代过程，难以并行化。但是和卷积处理这种极度耗时的计算相比，耗费时间又不是特别明显。所以，时间上的优化工作不多，大多是性能上的优化，就是改造的NMS更准确但更耗时了。 NMS就是一个检测结果的后处理环节，对冗余的检测框进行 ...
torchvision中的nms是如何实现的？ 知乎 目标检测 深度学习（Deep Learning） 物体检测
一般来说好像 NMS 用得比较多，WBF 是这个作者新提出的方法，貌似比较适合组合多个模型的输出。 这个东西是最近在 Kaggle 的一个竞赛里面看到一个大佬在用，我没有实际用过，我自己只用过 GluonCV 实现的 YOLOv3 模型中自带的 NMS。
我解答一下，题中 f m ω m f_ {m}\omega_ {m} 其实是阻力产生的动量矩，题中说是粘度摩擦系数，容易混淆，以为要从Stocks方程考虑粘度系数解释，非也，同时也不是传统上的意义上的摩擦系数定义，注意 f m f_ {m} 是有单位的 (N m s) \left ( Nms \right) ，再比如如下的例子:
非极大值抑制（Non Maximum Suppress，NMS）算法，其核心思想在于抑制非极大值的目标（去冗余），从而搜索出局部极大值的目标（找最优）。由于不同的目标框有不同的表示方式，因此NMS算法也具有不同的变体，本文通过目标检测的非极大抑制引入，简单讲述非极大抑制的思想以及其在边缘检测上的 ...
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