Advanced Two Stage AI Technique for Object Detection

Object detection in computer vision uses AI, mainly deep learning, to identify and locate objects in images or videos. It involves an AI system that spots various objects, determines their type, and marks their positions with bounding boxes. Built on advanced deep learning models like Convolutional Neural Networks (CNNs), YOLO, or Faster R-CNN, it excels in real-time detection. Trained on large datasets like COCO, it recognizes diverse objects across different scenes. It tackles challenges investigates challenges like varying object sizes, scales, lighting, and occlusion using techniques such as transfer learning, data augmentation, and model optimization for fast, accurate results. Keywords: Deep learning, YOLO / Faster R-CNN, bounding boxes, and COCO dataset

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Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-05-14
DOI
https://doi.org/10.55041/ijsrem47821
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Advanced Two Stage AI Technique for Object Detection

Shashank Tiwari
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Industrial Vision Systems and Defect Detection
article

Advanced Two Stage AI Technique for Object Detection

Shashank Tiwari
article en

Abstract

Object detection in computer vision uses AI, mainly deep learning, to identify and locate objects in images or videos. It involves an AI system that spots various objects, determines their type, and marks their positions with bounding boxes. Built on advanced deep learning models like Convolutional Neural Networks (CNNs), YOLO, or Faster R-CNN, it excels in real-time detection. Trained on large datasets like COCO, it recognizes diverse objects across different scenes. It tackles challenges investigates challenges like varying object sizes, scales, lighting, and occlusion using techniques such as transfer learning, data augmentation, and model optimization for fast, accurate results. Keywords: Deep learning, YOLO / Faster R-CNN, bounding boxes, and COCO dataset

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(05)
Openalex Percentile: Top 86%
Industrial Vision Systems and Defect Detection
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