A Frequency Domain-Enhanced Transformer for Nighttime Object Detection by Yaru Li, Li Shen

“…Our approach integrates physics-prior enhancement to improve the visibility of objects in low-light conditions, frequency domain feature extraction to capture structural information potentially lost in the spatial domain, and window cross-attention fusion that efficiently combines complementary features while reducing computational complexity, significantly improving detection performance without increasing the parameter count. …”
Get full text

Reinforcement Learning for Routing in Cognitive Radio Ad Hoc Networks by Hasan A. A. Al-Rawi, Kok-Lim Alvin Yau, Hafizal Mohamad, Nordin Ramli, Wahidah Hashim

Get full text

Property Graph Framework for Geographical Routes in Sports Training by Alen Rajšp, Iztok Fister

Get full text

A Review of IEEE 802.15.6 MAC, PHY, and Security Specifications by Sana Ullah, Manar Mohaisen, Mohammed A. Alnuem

Get full text

Performance prediction and optimization of a high-efficiency tessellated diamond fractal MIMO antenna for terahertz 6G communication using machine learning approaches by Kamal Hossain Nahin, Jamal Hossain Nirob, Akil Ahmad Taki, Md Ashraful Haque, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Reem Ibrahim Alkanhel, Hanaa A. Abdallah, Abdelhamied A. Ateya, Ahmed A. Abd El-Latif

Get full text

Toward an Efficient and Robust Process–Structure Prediction Framework for Filigree L-PBF 316L Stainless Steel Structures by Yu Qiao, Marius Grad, Aida Nonn

Get full text

Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation by Milad Shoryabi, Ahmad Hajipour, Afshin Shoeibi, Ali Foroutannia

Get full text

An Efficient Method for Offset Mitigation in Free-Space Optical Systems by Omar A. Saraereh, Imran Khan, Jeong Woo Lee

“…The system performance parameters such as the bit error rate (BER), mean square error (MSE), and computational complexity are evaluated. …”
Get full text

Bayesian solution to the inverse problem and its relation to Backus–Gilbert methods by Luigi Del Debbio, Alessandro Lupo, Marco Panero, Nazario Tantalo

“…In this work, we discuss how Backus–Gilbert methods, in particular the variation introduced by some of the authors, relate to the solution based on Gaussian Processes. Both methods allow computing spectral densities smearing with a kernel whose features depend on the detail of the algorithm. …”
Get full text

Maximum time between cardiac cycles in atrial fibrillation for assessing the risk of arterial thromboembolism by O. A. Germanova, A. V. Germanov, Yu. V. Shchukin

“…A similar trend was also observed in the analysis of arterial kinetic parameters.Conclusion. Not only the fact of AF presence is important for assessing the risk of arterial thromboembolism, but also its features. …”
Get full text

Research on the lightweight detection method of rail internal damage based on improved YOLOv8 by Xiaochun Wu, Shuzhan Yu

“…Firstly, the GhostHGNetV2 network is adopted as the feature extraction backbone, which reduces computational costs through structural optimization. …”
Get full text

FORECASTING THE INVESTMENT INDICATORS ON THE BASIS OF SOLUTION TREES by Olga V. Kitova, Igor B. Kolmakov, Ilya A. Penkov

“…The authors put forward several variants of implementing models designed by Python programming. Computer experiments were conducted to adjust model parameters that can guarantee acceptable results in forecasting investment indicators.…”
Get full text

Dataset on energy consumption in buildings within tropical climate based on design aspects of courtyardsGithub by Abdulbasit Almhafdy, Ashjan Al-Mutairi, Asma Al-Shargabi, Amal Al-Shargabi

Get full text

IoT enabled health monitoring system using rider optimization algorithm and joint process estimation by J. Prabin Jose, G. Jaffino, Mohammed Al Awadh, Koppula Srinivas Rao, Yan Yafang, Krishna Moorthy Sivalingam

Get full text

ADSTrack: adaptive dynamic sampling for visual tracking by Zhenhai Wang, Lutao Yuan, Ying Ren, Sen Zhang, Hongyu Tian

“…Moreover, the adaptive dynamic sampling strategy is a parameterless token sampling strategy that does not use additional parameters. We add several extra tokens as auxiliary tokens to the backbone to further optimize the feature map. …”
Get full text

Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

“…The model’s parameter count and computational complexity require reduction. …”
Get full text

DualCascadeTSF-MobileNetV2: A Lightweight Violence Behavior Recognition Model by Yuang Chen, Yong Li, Shaohua Li, Shuhan Lv, Fang Lin

“…Meanwhile, the model incorporates the efficient lightweight structure of MobileNetV2, significantly reducing the number of parameters and computational complexity. Experiments were conducted on three public violent behavior datasets, Crowd Violence, RWF-2000, and Hockey Fights, to verify the performance of the model. …”
Get full text

ET-Mamba: A Mamba Model for Encrypted Traffic Classification by Jian Xu, Liangbing Chen, Wenqian Xu, Longxuan Dai, Chenxi Wang, Lei Hu

“…During the fine-tuning phase, the agent attention mechanism is adopted in the feature extraction phase to achieve global information modeling at a low computational cost, and the SmoothLoss function is designed to solve the problem of the insufficient generalization ability of cross-entropy loss function during training. …”
Get full text

Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

“…First, owing to the issue that the Lagrange multiplier of the standard least squares support vector machine (LS-SVR) is directly proportional to the error term and solves the lack of sparsity, the maximal independent set of sample data in the feature space mapping set was extracted to realize the sparse of the training sample set and reduce the computational complexity of modeling. …”
Get full text

A Technique for Monitoring Mechanically Ventilated Patient Lung Conditions by Pieter Marx, Henri Marais

“…Results: Using statistical classification and regression models, the approach achieves 99.1% accuracy for ventilation mode classification, 97.5% accuracy for feature extraction, and 99.0% for predicting mechanical lung parameters. …”
Get full text