TY - JOUR T1 - Providing a Method for Object Detection Using a Combination Category AU - Seyed Ahad Zolfagharifar , Faramarz Karamizadeh and Hamid Parvin JO - Journal of Information and Computing Science VL - 4 SP - 270 EP - 280 PY - 2024 DA - 2024/01 SN - 11 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jics/22504.html KW - object detection systems, classification, pattern recognition, learning object, heuristic algorithms association rules. AB - The object detection systems in an image, refers to systems that will find an object in an image completely mechanized and automated. These systems are often searching a particular object (which is known) in a raw image. These systems are often involved in two separate categories: (a) image processing, and (b) pattern recognition. The first issue involves the extraction of meaningful and valuable features. While the second issue involved finding a suitable learning model, so that it separates the object data from non- object data in a favorable and acceptable way. In this study, we have reviewed by three-step method of learning objects and using a multi-layered combination model for detection and using heuristic algorithms association rules for feature selection step and finally using a combination category method similar to the intensification of the final step there. And by reviewing various evaluation models, we measured the quality of our models. In this study, we showed that using a majority vote model is the best way to detect an object.

Seyed Ahad Zolfagharifar , Faramarz Karamizadeh and Hamid Parvin. (2024). Providing a Method for Object Detection Using a Combination Category. Journal of Information and Computing Science. 11 (4). 270-280. doi: