Yubin Cho
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View article: Development of a Tractor Hydrostatic Transmission Efficiency Prediction Model Using Novel Hybrid Deep Kernel Learning and Residual Radial Basis Function Interpolator Model
Development of a Tractor Hydrostatic Transmission Efficiency Prediction Model Using Novel Hybrid Deep Kernel Learning and Residual Radial Basis Function Interpolator Model Open
This study proposes a data-efficient surrogate modeling approach for predicting hydrostatic transmission (HST) system efficiency in tractors using minimal data. Only 27 samples were selected from a dataset of 5092 measurements based on the…
View article: Machine Learning-Based Framework for Pre-Impact Same-Level Fall and Fall-from-Height Detection in Construction Sites Using a Single Wearable Inertial Measurement Unit
Machine Learning-Based Framework for Pre-Impact Same-Level Fall and Fall-from-Height Detection in Construction Sites Using a Single Wearable Inertial Measurement Unit Open
Same-level-falls (SLFs) and falls-from-height (FFHs) remain major causes of severe injuries and fatalities on construction sites. Researchers are actively developing fall-prevention systems requiring accurate SLF and FFH detection in const…
View article: Learned Image Compression and Restoration for Digital Pathology
Learned Image Compression and Restoration for Digital Pathology Open
Digital pathology images play a crucial role in medical diagnostics, but their ultra-high resolution and large file sizes pose significant challenges for storage, transmission, and real-time visualization. To address these issues, we propo…
View article: Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration
Enhanced Three-Axis Frame and Wand-Based Multi-Camera Calibration Method Using Adaptive Iteratively Reweighted Least Squares and Comprehensive Error Integration Open
The accurate transformation of multi-camera 2D coordinates into 3D coordinates is critical for applications like animation, gaming, and medical rehabilitation. This study unveils an enhanced multi-camera calibration method that alleviates …
View article: MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic Segmentation
MetaSeg: MetaFormer-based Global Contexts-aware Network for Efficient Semantic Segmentation Open
Beyond the Transformer, it is important to explore how to exploit the capacity of the MetaFormer, an architecture that is fundamental to the performance improvements of the Transformer. Previous studies have exploited it only for the backb…
View article: Deep-Learning-Based Recovery of Missing Optical Marker Trajectories in 3D Motion Capture Systems
Deep-Learning-Based Recovery of Missing Optical Marker Trajectories in 3D Motion Capture Systems Open
Motion capture (MoCap) technology, essential for biomechanics and motion analysis, faces challenges from data loss due to occlusions and technical issues. Traditional recovery methods, based on inter-marker relationships or independent mar…
View article: Cross-Aware Early Fusion With Stage-Divided Vision and Language Transformer Encoders for Referring Image Segmentation
Cross-Aware Early Fusion With Stage-Divided Vision and Language Transformer Encoders for Referring Image Segmentation Open
Referring segmentation aims to segment a target object related to a natural language expression. Key challenges of this task are understanding the meaning of complex and ambiguous language expressions and determining the relevant regions i…