GPU Accelerated Trilateral Filter for MR Image Restoration by Suthir Sriram, Nivethitha Vijayaraj, T. Srilekha, M. Praveena, Thangavel Murugan

“…The approach uses forward selection to identify 98 texture attributes while refining the selection process to find optimal regularity features. A two-phase classification system trains automation parameters using artificial neural networks together with support vector machines. …”
Get full text

GPU Acceleration for FHEW/TFHE Bootstrapping by Yu Xiao, Feng-Hao Liu, Yu-Te Ku, Ming-Chien Ho, Chih-Fan Hsu, Ming-Ching Chang, Shih-Hao Hung, Wei-Chao Chen

“…To address this challenge, hardware acceleration has emerged as a promising approach, aiming to achieve real-time computation across a wider range of scenarios. In line with this, our research focuses on designing and implementing a Graphic Processing Unit (GPU)-based accelerator for the third generation FHEW/TFHE bootstrapping scheme, which features smaller parameters and bootstrapping keys particularly suitable for GPU architectures compared to the other generations. …”
Get full text

Kans-Unet Model and Its Application in Image Patch-Shaped Detection by Xingsu Li, Zhong Li, Jianping Huang, Ying Han, Kexin Zhu, Bo Hao, Junjie Song, Yumeng Huo

“…It solves the problem of long model training time caused by insufficient computing power and provides a new method for the detection and analysis of abnormal features in power spectrum images.…”
Get full text

Exploring Trial-and-Error in Deep Learning: Initial Application to Isotope Detection in Mass Spectrometry by Qihong Jiao, Yuxiao Wang, Yongshuai Wang, Shiwei Sun, Xuefeng Cui

Get full text

ShadowFPN-YOLO: A Real-Time NMS-Free Detector for Remote Sensing Ship Detection by Xiao Yang, Ahmad Sufril Azlan Mohamed, Chuanchuan Wang

“…Experimental results demonstrate the strong performance of our method, achieving mAP values of 55.70 at 430 FPS on the DIOR-Ship dataset and 55.85 at 497 FPS on the HRSID dataset, all while maintaining the fewest parameters and the lowest computational cost compared to the latest YOLO models. …”
Get full text

An improved ShuffleNetV2 method based on ensemble self-distillation for tomato leaf diseases recognition by Shuiping Ni, Yue Jia, Mingfu Zhu, Mingfu Zhu, Yizhe Zhang, Wendi Wang, Shangxin Liu, Yawei Chen

Get full text

Modeling of a Novel T-Core Sensor with an Air Gap for Applications in Eddy Current Nondestructive Evaluation by Siquan Zhang

“…Compared to the finite element method (FEM), analytical approaches offer advantages, such as faster computation and high accuracy, enabling a comprehensive analysis of how sensor and material parameters influence defect detection outcomes. …”
Get full text

LCAMNet: a lightweight model for apple leaf disease classification in natural environments by Yuanyuan Jiao, Honghui Li, Xueliang Fu, Buyu Wang, Buyu Wang, Kaiwen Hu, Shuncheng Zhou, Daoqi Han

Get full text

Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition by Sk Mahmudul Hassan, Kumar Sekhar Roy, Ruhul Amin Hazarika, Mehbub Alam, Mithun Mukherjee

“…The proposed IEViT architecture extracts local as well as global features, which improves feature learning. The use of multiple filters with different kernel sizes efficiently uses computing resources to extract relevant features without the need for deeper networks. …”
Get full text

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions by Daniel A. Serino, Evan Bell, Marc Klasky, Ben S. Southworth, Balasubramanya Nadiga, Trevor Wilcox, Oleg Korobkin

Get full text

ROSE-BOX: A Lightweight and Efficient Intrusion Detection Framework for Resource-Constrained IIoT Environments by Silin Peng, Yu Han, Ruonan Li, Lichen Liu, Jie Liu, Zhaoquan Gu

“…Furthermore, to reduce computing resource requirements and latency while improving detection performance, Bayesian optimization is applied to fine-tune the parameters of XGBoost (BO-XGBoost) to obtain the best detection results. …”
Get full text

Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest by X Peng, C Chen, L Yu, X Kong, B Sun

“…To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
Get full text

Design of an Iterative Method for Malware Detection Using Autoencoders and Hybrid Machine Learning Models by Rijvan Beg, R. K. Pateriya, Deepak Singh Tomar

Get full text

Epileptic Seizure Detection in EEG Signals Using Machine Learning and Deep Learning Techniques by Hepseeba Kode, Khaled Elleithy, Laiali Almazaydeh

Get full text

Enhanced Conditional GAN for High-Quality Synthetic Tabular Data Generation in Mobile-Based Cardiovascular Healthcare by Malak Alqulaity, Po Yang

Get full text

SPL-YOLOv8: A Lightweight Method for Rape Flower Cluster Detection and Counting Based on YOLOv8n by Yue Fang, Chenbo Yang, Jie Li, Jingmin Tu

“…First, the model introduces StarNet as a lightweight backbone network for efficient feature extraction, significantly reducing computational complexity and parameter counts. …”
Get full text

BDK-YOLOv8: An Enhanced Algorithm for UAV Infrared Image Object Detection by Nan Xiao, Xianggong Hong, Zixuan Zheng

“…First, a new C2f-DCNv3 module is introduced to reduce parameter redundancy and enhance feature extraction. …”
Get full text

Online Attentive Kernel-Based Off-Policy Temporal Difference Learning by Shangdong Yang, Shuaiqiang Zhang, Xingguo Chen

Get full text

DCD-FPI: A Deformable Convolution-Based Fusion Network for Unmanned Aerial Vehicle Localization by Yufei He, Feiyang Chen, Jiahao Chen, Jiqi Fan, Enhui Zheng

“…Moreover, our model reduces computational complexity from 14.28 GFLOPS to 11.54 GFLOPS and parameter quantity from 14.76 M to 13.96 M.…”
Get full text

Finite-size effects in molecular simulations: a physico-mathematical view by Benedikt M. Reible, Carsten Hartmann, Luigi Delle Site

“…Here this feature is treated employing the same statistical mechanics framework developed for the first problem.…”
Get full text