对于FGVC具有类别外数据的半监督学习
IEEE transactions on pattern analysis and machine intelligence
|October 6, 2023
概括
本研究引入了一种新的半监督学习 (SSL) 方法,用于细粒度视觉分类 (FGVC),通过利用层次类别结构,有效利用类别之外的未标记数据. 该方法实现了强大的性能和最先进的结果.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 人工智能的人工智能
背景情况:
- 目前的细粒度视觉分类 (FGVC) 方法主要依赖于完全监督的学习,需要广泛的专家标签.
- 半监督学习 (SSL) 通过利用未标记的数据提供了一个有希望的替代方案,但现有的SSL范式在FGVC.
- 目前的SSL对FGVC的有效性受限于假设类别内未标记的数据.
研究的目的:
- 为细粒度视觉分类 (FGVC) 开发一种新的半监督学习 (SSL) 方法,有效地纳入类别之外的未标记数据.
- 利用细粒度类别的固有层次结构来提高SSL性能.
- 在层次框架内引入用于样本间一致性规范化和伪关系生成的新策略.
主要方法:
- 专门为FGVC提出了一个新的SSL设计,该设计利用了类别之外的数据.
- 假设并利用细粒度类别 (例如,系谱树) 的自然等级结构.
- 通过预测类别层次结构中的样本关系来优化SSL,引入一致性规范化和伪关系生成策略.
主要成果:
- 提出的方法在处理类别之外的未标记数据时显示出显著的稳定性.
- 该方法可以与现有方法集成,提高其性能.
- 综合方法在细粒度视觉分类方面取得了最先进的结果.
结论:
- 新的SSL方法有效地利用等级结构来克服FGVC中类别外数据的局限性.
- 该方法提供了一个强大的和可适应的解决方案,用于提高FGVC的性能,使用有限的标记数据.
- 这项工作为复杂的视觉分类任务推进了SSL技术,为更高效和更准确的模型铺平了道路.
相关概念视频
01:11How Data are Classified: Categorical Data
33.9K
A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
33.9K
01:26Classification of Systems-I
194
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
194
01:31Classification of Systems-II
154
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
154
01:29Aggregates Classification
332
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
332
01:30Classification of Signals
488
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
488
01:22Force Classification
1.2K
Forces play a crucial role in the study of physics and engineering. They are essential in describing the motion, behavior, and equilibrium of objects in the physical world. Forces can be classified based on their origin, type, and direction of action.
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
Contact and non-contact forces are two of the most widely used categories of forces. As the name suggests, contact forces require physical contact between two objects to act upon each other. Examples of contact forces include frictional,...
1.2K