A 3D Face Recognition Algorithm Directly Applied to Point Clouds by Xingyi You, Xiaohu Zhao

“…Firstly, we introduce a learning framework guided by a small amount of real face data based on morphable models with Gaussian processes. …”
Get full text

A Survey on Immersive Cyber Situational Awareness Systems by Hussain Ahmad, Faheem Ullah, Rehan Jafri

“…However, these systems face data occlusion and convolution issues due to the burgeoning complexity, dimensionality, and heterogeneity of cybersecurity data, which damages cyber situational awareness of end-users. …”
Get full text

Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The selected data set is pre-processed and feature selection for the optimization for the improvement in accuracy, and automation decision making the framework of the convolution neural network along with the ensemble boosted tree classifier developed is optimized using the jellyfish optimization and Recurrent Neural Network and Long Short-Term Memory (RNN-LSTM) model for the recognition of patterns and numerical vectors in the real-world data after processing of output then it is sent back as the input for the recurrent network to make the decision in the shipbuilding process. …”
Get full text

Equivalent force model of deformation induced by oil and gas reservoir development and its volume boundary element method solution by Xuehao PEI, Yuetian LIU, Liang XUE

“…It eliminates the need for meshing outside the reservoir, achieves significantly improved solution accuracy, and provides a new technical framework for simulating deformation induced by reservoir development.…”
Get full text

Research on AC–DC High-Frequency Interaction Mechanism and Valve-Side High-Frequency Oscillation Suppression Strategy of Flexible HVDC Converter by Liwu Tan, Yang Zhang, Yanan Wu, Yu An, Yuhan Huang

“…The high-frequency modeling framework and suppression strategies presented in this study provide substantial improvements in both theoretical understanding and practical mitigation techniques for high-frequency oscillations in flexible HVDC systems, offering enhanced stability for modern power transmission infrastructure.…”
Get full text

Bayesian Optimized of CNN-M-LSTM for Thermal Comfort Prediction and Load Forecasting in Commercial Buildings by Chi Nghiep Le, Stefan Stojcevski, Tan Ngoc Dinh, Arangarajan Vinayagam, Alex Stojcevski, Jaideep Chandran

“…The hyperparameter fine tuning framework applied Bayesian optimization to enhance output prediction by modifying model properties with data characteristics. …”
Get full text

Resilience Analysis of Urban Road Networks Based on Adaptive Signal Controls: Day-to-Day Traffic Dynamics with Deep Reinforcement Learning by Wen-Long Shang, Yanyan Chen, Xingang Li, Washington Y. Ochieng

“…This study proposes a novel adaptive signal control strategy based on a doubly dynamic learning framework, which consists of deep reinforcement learning and day-to-day traffic dynamic learning, to improve the network performance by adjusting red/green time split. …”
Get full text

Comparing UNet configurations for anthropogenic geomorphic feature extraction from land surface parameters. by Sarah Farhadpour, Aaron E Maxwell

“…We argue that one of the positive attributes of UNet is that it can be treated as a general framework that can easily be modified.…”
Get full text

Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…The key insights the current research provides are the necessity of early intervention and directed training support in the educational domain. The EffiXNet framework offers a robust, scalable, and efficient solution for predicting student performance, with potential applications in academic institutions worldwide.…”
Get full text

SDFA-Net: Synergistic Dynamic Fusion Architecture With Deformable Attention for UAV Small Target Detection by Yunsong Qi, Hengwei Cao

“…This study proposes an enhanced detection algorithm based on a real-time detection transformer framework (RT-DETR). Address the problem of leakage and misjudgment in small-target detection in aerial images. …”
Get full text

Research and application of mining AI video edge computing technology by ZHANG Liya, HAO Bonan, MA Zheng, YANG Zhifang

“…A lightweight software development kit (SDK) framework based on the register machine was proposed to decouple operators, improving the parallel computing ability of the algorithms and reducing the storage requirements of the SDK. …”
Get full text

Towards Synthetic Augmentation of Training Datasets Generated by Mobility-on-Demand Service Using Deep Variational Autoencoders by Martin Gregurić, Filip Vrbanić, Edouard Ivanjko

“…The proposed 2-dimensional convolution VAE framework has achieved clustering results comparable with the other analysed approaches. …”
Get full text

Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…We propose MCSS (multi-view collaborative training and self-supervised learning), a novel framework that harnesses both multi-view collaborative training and self-supervised learning specifically for group recommendations. …”
Get full text

Turing patterns across geometries: A proven DSC-ETDRK4 solver from plane to sphere by Kolade M. Owolabi, Edson Pindza, Eben Maré

“…This paper presents a unified and robust numerical framework that combines the Discrete Singular Convolution (DSC) method for spatial discretization with the Exponential Time Differencing Runge–Kutta (ETDRK4) scheme for temporal integration to solve reaction–diffusion systems. …”
Get full text

Partial feature reparameterization and shallow-level interaction for remote sensing object detection by Minh Tai Pham Nguyen, Quoc Duy Nam Nguyen, Hoang Viet Anh Le, Minh Khue Phan Tran, Tadashi Nakano, Thi Hong Tran

“…Firstly, an extraction block is proposed called PRepConvBlock that leverages reparameterization convolution and partial feature utilization to effectively reduce the complexity in convolution operations, allowing for the utilization of larger kernel sizes in order to form the longer interactions between features and significantly expand receptive fields. …”
Get full text

FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…This algorithm is developed based on the YOLOv8n framework with the aim of improving accuracy and model lightweight design. …”
Get full text

DDI-KGAT: A Graph Attention Network on Biomedical Knowledge Graph for the Prediction of Drug-Drug Interactions by Iqra Naseer Kundi, Shahzad Amin Sheikh, Fahad Mumtaz Malik, Kamran Aziz Bhatti

“…Our study highlights the potential of attention mechanisms in knowledge graph-based drug combination prediction, and we believe that KGAT can serve as a valuable framework for future research in this field.…”
Get full text

A systematic review on the associations between built environment and mental health among older people by Yongkang Chen, Lizhen Xu, Xiangfen Cui, Haoran Yang, Haoran Yang, Yiling Liu, Xin Gao, Jianhong Huang

“…We have established a quantifiable evaluation framework for BE elements, addressing the limitations of previous studies that relied on subjective perception measurements. …”
Get full text

Deep learning-enabled exploration of global spectral features for photosynthetic capacity estimation by Xianzhi Deng, Xiaolong Hu, Liangsheng Shi, Chenye Su, Jinmin Li, Shuai Du, Shenji Li

“…Our model provides a new framework for interpreting spectral information and accurately estimating photosynthetic capacity.…”
Get full text

Self-Supervised Learning of End-to-End 3D LiDAR Odometry for Urban Scene Modeling by Shuting Chen, Zhiyong Wang, Chengxi Hong, Yanwen Sun, Hong Jia, Weiquan Liu

“…To address these challenges, we propose UnMinkLO-Net, an end-to-end self-supervised LiDAR odometry framework. Our method is as follows: (1) we efficiently encode 3D point cloud structures using voxel-based sparse convolution, and (2) we model inherent alignment uncertainty via covariance matrices, enabling novel self-supervised loss based on uncertainty modeling. …”
Get full text