In machine learning, the model is not as complicated as possible. Good generalization
ability means that the model not only performs well on the training data set, but also can …

Fatigue life prediction is critical for ensuring the safe service and the structural integrity of
mechanical structures. Although data-driven approaches have been proven effective in …

In this paper, we propose a real-time and accurate automatic license plate recognition
(ALPR) approach. Our study illustrates the outstanding design of ALPR with four insights:(1) …

Biochar has demonstrated significant promise in addressing heavy metal contamination and
methane (CH4) emissions in paddy soils; however, achieving a synergy between these two …

Abstract Person Recognition based on Gait Model (PRGM) and motion features is are
indeed a challenging and novel task due to their usages and to the critical issues of human …

Existing fine-tuning methods for computer vision tasks primarily focus on re-weighting the
knowledge learned from the source domain during pre-training. They aim to retain beneficial …

Data augmentation strategies have always been important in machine learning techniques
and play a unique role in model performance optimization processes. Therefore, in recent …

Background Tertiary lymphoid structures (TLSs) are potential prognostic indicators.
Radiomics may help reduce unnecessary invasive operations. Purpose To analyze the …

Additive manufacturing features rapid production of complicated shapes and has been
widely employed in biomedical, aeronautical and aerospace applications. However, additive …

Objective: Preoperative differentiation between parotid Warthin's tumor (WT) and
pleomorphic adenoma (PMA) is crucial for treatment decisions. The purpose of this study …