output
20232025
most citedGLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning

16 citations

4 papers

cs.CV2025★ 4 cited

CORE-ReID V2: Advancing the Domain Adaptation for Object Re-Identification with Optimized Training and Ensemble Fusion

Trinh Quoc Nguyen, Oky Dicky Ardiansyah Prima, Syahid Al Irfan +2

This study presents CORE-ReID V2, an enhanced framework building upon CORE-ReID. The new framework extends its predecessor by addressing Unsupervised Domain Adaptation (UDA) challe…

cs.CV2024★ 1 cited

The object detection model uses combined extraction with KNN and RF classification

Florentina Tatrin Kurniati, Daniel HF Manongga, Irwan Sembiring +2

Object detection plays an important role in various fields. Developing detection models for 2D objects that experience rotation and texture variations is a challenge. In this resea…

cs.CV2024★ 16 cited

GLCM-Based Feature Combination for Extraction Model Optimization in Object Detection Using Machine Learning

Florentina Tatrin Kurniati, Daniel HF Manongga, Eko Sediyono +2

In the era of modern technology, object detection using the Gray Level Co-occurrence Matrix (GLCM) extraction method plays a crucial role in object recognition processes. It finds…

cs.CV2023★ 1 cited

Object Classification Model Using Ensemble Learning with Gray-Level Co-Occurrence Matrix and Histogram Extraction

Florentina Tatrin Kurniati, Daniel HF Manongga, Eko Sediyono +2

In the field of object classification, identification based on object variations is a challenge in itself. Variations include shape, size, color, and texture, these can cause probl…