Object detection and classification by cascade object training

Ahmed Masud Chowdhury, J. Jabin, Erteza Tawsif Efaz, Md Ehtesham Adnan, Ashfia Binte Habib
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引用次数: 3

Abstract

Computer Vision (CV) has become ubiquitous in smart systems for detecting and labeling objects, starting from social media platforms to autonomous vehicles. It requires extensive computation and image processing. In this paper, a model is processed and used to detect various colored cups with saucers from a set of different objects. The system is trained using Cascade Trainer Graphical User Interface (GUI), and the testing is done utilizing MATLAB, discussed in detail. Finally, the model is tested for its efficacy on the S32V234 Evaluation Board (EVB). Our proposed system accomplished its goal by identifying and tagging the objects of interest with maximum possible accuracy.
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通过级联目标训练进行目标检测和分类
从社交媒体平台到自动驾驶汽车,计算机视觉(CV)在检测和标记物体的智能系统中已经无处不在。它需要大量的计算和图像处理。本文对一个模型进行处理,并用于从一组不同的物体中检测不同颜色的杯碟。利用级联训练器图形用户界面(GUI)对系统进行了训练,并利用MATLAB对系统进行了测试。最后,在S32V234评估板(EVB)上测试了该模型的有效性。我们提出的系统通过尽可能准确地识别和标记感兴趣的对象来实现其目标。
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