Spatiotemporal Fusion Algorithm Based on Multikernal Adaptive Network by Qiuhui Wang, Qiong Ran, Ke Zheng, Jiaxin Li

“…The network incorporates our proposed Dynamic Visual Processing Module (DVPM) to achieve adaptive perception and intelligent fusion of multi-scale geophysical features. …”
Get full text

DAWN: Designing Distributed Agents in a Worldwide Network by Zahra Aminiranjbar, Jianan Tang, Qiudan Wang, Shubha Pant, Mahesh Viswanathan

“…The rapid evolution of Large Language Models (LLMs) has transformed them from basic conversational tools into sophisticated entities capable of complex reasoning and decision-making. …”
Get full text

Video Anomaly Detection Methods: a Survey by WU Peichen, YUAN Lining, GUO Fang, LIU Zhao

“…Furthermore, it compares and evaluates models using benchmark datasets and common evaluation standards such as frame-level and pixel-level standards, and conducts intra-class comparisons based on performance results, followed by analysis of the outcomes. …”
Get full text

An Effective Feature Extraction Method for Tomato Leafminer - Tuta Absoluta (Meyrick) (Lepidoptera: Gelechiidae) Classification by Tahsin Uygun, Serhat Kiliçarslan, Cemil Közkurt, Mehmet Metin Ozguven

“…Using a hybrid approach, features were extracted through Convolutional Neural Networks (CNNs) with transfer learning and classified using traditional machine learning techniques. …”
Get full text

A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…These electrode channels are used to construct a Functional Brain Network (FBN), from which the topological feature set is extracted. …”
Get full text

Probabilistic Estimation of Parameters for Lubrication Application with Neural Networks by Stefan Paschek, Frederic Förster, Martin Kipfmüller, Michael Heizmann

“…A combination of two feed-forward neural networks was used to estimate both the value and the standard deviation of selected features. …”
Get full text

Research on deep learning model for stock prediction by integrating frequency domain and time series features by Wenjie Sun, Jianhua Mei, Shengrui Liu, Chunhong Yuan, Jiaxuan Zhao

“…The StockMixer with ATFNet model proposed in this paper integrates both time-domain and frequency-domain features. By fusing information from both domains, the deep neural network significantly improves prediction accuracy and reliability. …”
Get full text

VBCNet: A Hybird Network for Human Activity Recognition by Fei Ge, Zhenyang Dai, Zhimin Yang, Fei Wu, Liansheng Tan

“…Meanwhile, VBCNet employs a convolutional feed-forward network instead of the traditional feed-forward network to enhance the model’s ability to process local and multi-scale features. …”
Get full text

Bearing Lifespan Reliability Prediction Method Based on Multiscale Feature Extraction and Dual Attention Mechanism by Xudong Luo, Minghui Wang

“…Evaluation results based on mean absolute error (MAE) and root mean square error (RMSE) indicated that the dual attention mechanism effectively focused on key features, optimized feature extraction, and improved prediction performance. …”
Get full text

Degree Distribution of Evolving Network with Node Preference Deletion by Yue Xiao, Xiaojun Zhang

“…The ESPR method makes the evolving network’s topological structure and statistical properties consistent with those observed in the natural evolution process, ensures the theoretical results of the degree distribution of the evolving network model, and overcomes the limitations of using empirical methods for approximate analysis. …”
Get full text

Leveraging Graph Neural Networks for IoT Attack Detection by Mevlüt Uysal, Erdal Özdoğan, Onur Ceran

“…The proposed model preprocesses data by standardization, handling missing values, and encoding categorical features. It leverages GNNs to model spatial dependencies and interactions within IoT networks and utilizes XGBoost to distill complex features for predictive analysis. …”
Get full text

Improving kidney segmentation in pathological images: a multiscale approach to resolve fragmentation and incomplete boundaries by Muhammad Wajeeh Us Sima, Chengliang Wang, Muhammad Arshad, Jamshed Ali Shaikh, Reem Ibrahim Alkanhel, Dina S. M. Hassan, Ammar Muthanna

“…InFeNet combines advanced Residual Networks with multi-scale feature extraction and refinement, incorporating correlations among spatial features to optimize feature maps. …”
Get full text

Research on Bearing Fault Diagnosis Method for Varying Operating Conditions Based on Spatiotemporal Feature Fusion by Jin Wang, Yan Wang, Junhui Yu, Qingping Li, Hailin Wang, Xinzhi Zhou

“…To address this issue, this paper proposes a spatiotemporal feature fusion domain-adaptive network (STFDAN) framework for bearing fault diagnosis under varying operating conditions. …”
Get full text

A study of pipeline parallelism in deep neural networks by Gabriel Núñez, Hairol Romero-Sandí, Elvis Rojas, Esteban Meneses

“…We analyze important aspects of these libraries such as their implementation and features. In addition, we evaluated them experimentally, carrying out parallel trainings and taking into account aspects such as the number of stages in the training pipeline and the type of balance. …”
Get full text

Neural network models for whisper to normal speech conversion by Cézar Yamamura, Paulo Scalassara, Marco Oliveira, Aníbal Ferreira

“…The system is developed using multilayer perceptron networks and two types of generative adversarial networks. …”
Get full text

cytoNet: Spatiotemporal network analysis of cell communities. by Arun S Mahadevan, Byron L Long, Chenyue W Hu, David T Ryan, Nicolas E Grandel, George L Britton, Marisol Bustos, Maria A Gonzalez Porras, Katerina Stojkova, Andrew Ligeralde, Hyeonwi Son, John Shannonhouse, Jacob T Robinson, Aryeh Warmflash, Eric M Brey, Yu Shin Kim, Amina A Qutub

“…We introduce cytoNet, a cloud-based tool to characterize cell populations from microscopy images. cytoNet quantifies spatial topology and functional relationships in cell communities using principles of network science. Capturing multicellular dynamics through graph features, cytoNet also evaluates the effect of cell-cell interactions on individual cell phenotypes. …”
Get full text

Natural Course of Electrocardiographic Features in Arrhythmogenic Right Ventricular Cardiomyopathy and Their Relation to Ventricular Arrhythmic Events by Anneli Svensson, Henrik Kjaerulf Jensen, Machteld J. Boonstra, Marianne Tétreault‐Langlois, Pia Dahlberg, Henning Bundgaard, Alex Hørby Christensen, Rebecca T. Rylance, Jesper H. Svendsen, Julia Cadrin‐Tourigny, Anneline S. J. M. te Riele, Pyotr G. Platonov

Get full text

An IoT intrusion detection framework based on feature selection and large language models fine-tuning by Huan Ma, Wan Zhang, Dalong Zhang, Baozhan Chen

“…At its core is a multi-stage feature selection algorithm combining Minimum Redundancy Maximum Relevance algorithm (mRMR) and a Pearson Correlation Coefficient (PCC)-improved Covariance Matrix Adaptation Evolution Strategy algorithm (CMA-ES). …”
Get full text

An egonet based approach to effective weighted network comparison by Carlo Piccardi

“…Abstract With the impressive growth of network models in practically every scientific and technological area, we are often faced with the need to compare graphs, i.e., to quantify their (dis)similarity using appropriate metrics. …”
Get full text

Efficient Deterministic Anchor Deployment for Sensor Network Positioning by Yongle Chen, Ci Chen, Hongsong Zhu, Limin Sun

“…Sensor network positioning systems have been extensively studied in recent years. …”
Get full text