Object Detection in Pytorch Using Mask R-CNN


Authors : Tobi Makinde

Volume/Issue : Volume 9 - 2024, Issue 6 - June

Google Scholar : https://rb.gy/hod98n

Scribd : https://rb.gy/oln0dl

DOI : https://doi.org/10.38124/ijisrt/IJISRT24JUN1069

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Abstract : This research paper aims to investigate the idea of object detection in PyTorch employing the most widely known object detection and localization algorithm that employs image segmentation techniques and deep learning approach, which is Mask Region-based Convolutional Neural Network. Mask R-CNN is widely used in many fields, such as industrial and medical applications, due to its ability to accurately identify objects and generate segmentation masks for each instance. The Mask R-CNN algorithm combines the region proposal generation and object classification stages of Faster R-CNN with an additional branch for pixel-level segmentation.

Keywords : Convolutional Neural Network, Object Detection, Pre-trained Model, PyTorch, Object Detection, Image Preprocessing, Pandas, NumPy, Pretrained Model, Mask Region-Based Convolutional Neural Network.

References :

  1. Widiyanto, S., Nugroho, D. P., Daryanto, A., Yunus, M., & Wardani, D. T.. (2021, January 1). Monitoring the Growth of Tomatoes in Real Time with Deep Learning-based Image Segmentation. https://scite.ai/reports/10.14569/ijacsa.2021.0121247.
  2. Kim, J., Kwon, S., Fu, J., & Park, J. (2022, October 14). Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN. https://scite.ai/reports/10.3390/jimaging8100283.
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  7. Su, Peifeng, J. (2022, January 25). New particle formation event detection with Mask R-CNN. https://scite.ai/reports/10.5194/acp-22-1293-2022

This research paper aims to investigate the idea of object detection in PyTorch employing the most widely known object detection and localization algorithm that employs image segmentation techniques and deep learning approach, which is Mask Region-based Convolutional Neural Network. Mask R-CNN is widely used in many fields, such as industrial and medical applications, due to its ability to accurately identify objects and generate segmentation masks for each instance. The Mask R-CNN algorithm combines the region proposal generation and object classification stages of Faster R-CNN with an additional branch for pixel-level segmentation.

Keywords : Convolutional Neural Network, Object Detection, Pre-trained Model, PyTorch, Object Detection, Image Preprocessing, Pandas, NumPy, Pretrained Model, Mask Region-Based Convolutional Neural Network.

Video Explanation for Published paper

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