YOLO vs CNN : A Comparative Study on Object Detection

Abstract—With the availability of large amount of data and increasing demand of digitizing the visual systems, lot of research on object detection techniques has been the foremost requirement since last ten years. As the technological advancements are pacing at such a higher rate with increasing computational power and new architectures for CNN has already been proposed in a successive manner to enhance the detection techniques. For Real time Object identification, CNN has proposed several architectures but YOLO proves itself better than others based on the speed of identification. This paper presents the brief overview and comparative analysis of various object detection techniques like SSD, RCNN, YOLO and their subsequent versions for different applications. On comparing, it is found that single stage detectors outperform two stage detectors. Keywords—Pascal VOC, MS COCO, YOLO, CNN, Object detection, Object Recognition, SSD.

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2024-11-08
DOI
https://doi.org/10.55041/ijsrem38457
Citations
1
Primary Topic
Advanced Neural Network Applications
Type
article
Field-Weighted Citation Impact
0.25
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article

YOLO vs CNN : A Comparative Study on Object Detection

Meha Shrivastava, R. Gupta
1 citations
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Advanced Neural Network Applications
0.25
article

YOLO vs CNN : A Comparative Study on Object Detection

Meha Shrivastava, R. Gupta
article en
1 citations

Abstract

Abstract—With the availability of large amount of data and increasing demand of digitizing the visual systems, lot of research on object detection techniques has been the foremost requirement since last ten years. As the technological advancements are pacing at such a higher rate with increasing computational power and new architectures for CNN has already been proposed in a successive manner to enhance the detection techniques. For Real time Object identification, CNN has proposed several architectures but YOLO proves itself better than others based on the speed of identification. This paper presents the brief overview and comparative analysis of various object detection techniques like SSD, RCNN, YOLO and their subsequent versions for different applications. On comparing, it is found that single stage detectors outperform two stage detectors. Keywords—Pascal VOC, MS COCO, YOLO, CNN, Object detection, Object Recognition, SSD.

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 08(11)
Rajiv Gandhi Technical University (IN)
Openalex Percentile: Top 45%
Advanced Neural Network Applications
0.25
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