To Develop Multi-Object Detection and Recognition Using Improved GP-FRCNN Method
Yazarlar (4)
Ganesh Babu Loganathan
Tishk International University, Irak
Tishk International University, Irak
Tooraj Hassan Fatah
Noble Institute of Technology, Irak
Noble Institute of Technology, Irak
Dr. Öğr. Üyesi Elham Tahsın Yasın YASIN Noble Institute of Technology, Irak
Nawroz Ibrahim Hamadamen
Salahaddin University-Erbil, Irak
Salahaddin University-Erbil, Irak
| Bildiri Türü | Tebliğ/Bildiri | Bildiri Dili | İngilizce |
| Bildiri Alt Türü | Tam Metin Olarak Yayınlanan Tebliğ (Uluslararası Kongre/Sempozyum) | ||
| Bildiri Niteliği | Alanında Hakemli Uluslararası Kongre/Sempozyum | ||
| DOI Numarası | 10.1109/ICSSS54381.2022.9782296 | ||
| Kongre Adı | 2022 8th International Conference on Smart Structures and Systems (ICSSS) | ||
| Kongre Tarihi | 21-04-2022 / | ||
| Basıldığı Ülke | Hindistan | Basıldığı Şehir | Chennai |
| Bildiri Linki | https://doi.org/10.1109/icsss54381.2022.9782296 | ||
| UAK Araştırma Alanları |
Bilgi Güvenliği ve Kriptoloji
Görüntü İşleme
Yapay Zeka
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| Özet |
| The Region-based Convolutional Neural Network (R-CNN), which is more rapid, has been recognized as the best detection algorithm. With our design basis for Faster RCNN (FRCNN), the designers reclassify the proposed object recognition changes with just a rough spatial estimate of the incident. The researchers solve problems such as delicate to complex environments and its principles are derived reductions each time it is -actually confronted with noisier initiatives. Through which designers categorize proposed changes to object recognition using a rough geometric estimate of the scene. This simple expansion requires complex changes of scale, which the authors describe in their entirely throughout this study. Moreover, Geometric Proposals with FRCNN (GP-FRCNN) performed relatively well on small and large things, which has always been a problem for computer vision algorithms. Any use of GP-FRCNN … |
| Anahtar Kelimeler |
| Underwater image | GP-FRCNN | Object recognition and detection | Complex environments |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 4 |
| Google Scholar | 13 |