基于上下文意识的Sketch-DeepNet架构用于AIoT中的手绘草图分类和识别
Safdar Ali1, Nouraiz Aslam1, DoHyeun Kim2
1Department of Software Engineering, University of Lahore, Lahore, Punjab, Pakistan.
PeerJ. Computer science
|June 22, 2023
概括
这项研究介绍了Sketch-DeepNet,一个卷积神经网络 (CNN),用于识别手绘草图. 在TU-柏林数据集上,Sketch-DeepNet实现了95.05%的准确性,超过了现有的方法和人类识别的草图分类.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 机器学习 机器学习
背景情况:
- 人类素描识别是高效的,但由于细节性较低,对计算机来说具有挑战性.
- 像SIFT和BoW这样的现有方法复杂且耗时.
- 深度神经网络 (DNN) 由于其性质而难以处理草图数据,需要专门的方法.
研究的目的:
- 开发一种有效的深度学习模型,用于准确的草图识别.
- 解决当前计算机视觉模型在理解手绘草图方面的局限性.
- 提高AIoT应用的草图分类系统的性能.
主要方法:
- 提出了一个新的卷积神经网络 (CNN) 架构,命名为Sketch-DeepNet.
- 利用柏林理工大学的数据集进行培训和评估草图分类模型.
- 对比了Sketch-DeepNet的性能与已建立的素描识别方法和人类准确性.
主要成果:
- 在TU-柏林数据集上,Sketch-DeepNet实现了95.05%的分类准确度.
- 拟议的模型显著优于现有的方法,包括DeformNet,Sketch-DNN,Sketch-a-Net,SketchNet,Thinning-DNN,CNN-PCA-SVM和混合CNN.
- 在同一数据集上,Sketch-DeepNet超过了人类识别准确度 (73%).
结论:
- 开发的Sketch-DeepNet架构在草图识别任务中表现出卓越的性能.
- 这一进步对于开发强大的人工智能物 (AIoT) 系统至关重要.
- 这些发现突出了专门的CNN在解释低细节图形表示的潜力.
相关概念视频
01:25Neural Circuits
1.3K
Neural circuits and neuronal pools are two of the main structures found in the nervous system. Neural circuits are networks of neurons that work together to carry out a specific task or process. They consist of interconnected neurons and glial cells, which provide structural and metabolic support.
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
Neuronal pools are collections of nerve cells with similar functions and interact through chemical and electrical signals. These pools include both interneurons (the central neural circuit nodes that...
1.3K
01:19High-Level and Low-Level Awareness
293
Controlled processes in human consciousness represent high-alert mental states where individuals deliberately focus their attention on achieving specific goals. Controlled processes can be seen in situations like mastering new technology, where a person might become so absorbed that they ignore surrounding distractions. Such processes involve selective attention, requiring one to concentrate on particular elements of experience while disregarding others. These are governed by executive...
293
01:20Parallel Processing
186
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
186
01:26Classification of Systems-I
221
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:
221
01:24Natural and Artificial Concepts
201
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
201