Optimizing unsupervised feature engineering and classification pipelines for differentiated thyroid cancer recurrence prediction by Emmanuel Onah, Uche Jude Eze, Abdullahi Salahudeen Abdulraheem, Ugochukwu Gabriel Ezigbo, Kosisochi Chinwendu Amorha, Fidele Ntie-Kang

“…This study aimed to enhance predictive performance by refining feature engineering and evaluating a diverse ensemble of machine learning models using the UCI DTC dataset. …”
Get full text

DP-FWCA: A Prompt-Enhanced Model for Named Entity Recognition in Educational Domains by Zhenkai Qin, Dongze Wu, Jiajing He, Jingming Xie, Aimin Wei

“…Our approach integrates domain-adaptive prompting to direct attention toward critical educational semantics, BERT-based contextual embeddings for robust representation learning, multi-scale convolutional neural networks (CNNs) with gated feature fusion to capture fine-grained local features, bidirectional LSTM networks augmented with self-attention to model long-range dependencies, and conditional random fields (CRFs) for structured sequence labeling. …”
Get full text

Intelligent Waste Management Using WasteIQNet With Hierarchical Learning and Meta-Optimization by Sakshi Tiwari, Snigdha Bisht, Kanchan Sharma

Get full text

Genotypic and Phenotypic Association of Agronomic Features in Triticale Genotypes under Drought Stress Conditions by Hassan Basiri, Omid Alizadeh, Forud Bazrafshan, Mehdi Zare, Mohammad Yazdani

“…Resistance to drought stress is a complex process that includes a network of plant responses at the physiological and molecular levels that have not yet been properly discovered and understood. …”
Get full text

A Global Irradiance Prediction Model Using Convolutional Neural Networks, Wavelet Neural Networks, and Masked Multi-Head Attention Mechanism by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Salah Hannechi

“…The CNN extracts spatial and local features, WNN performs frequency decomposition to capture multi-scale variations, and MMHA models temporal dependencies while encoding positional information.The model is trained and evaluated on a real-world climatic dataset from Tunisia, collected over eight years. …”
Get full text

A Closest Resemblance Classifier with Feature Interval Learning and Outranking Measures for Improved Performance by Nabil Belacel

“…To improve robustness, we incorporate outranking measures, which reduce the impact of noise and uncertainty through pairwise comparisons of alternatives across features. We evaluate our classifiers on multiple UCI repository datasets and compare them with established methods, including k-Nearest Neighbors (k-NN), Support Vector Machine (SVM), Random Forest (RF), Neural Networks (NNs), Naive Bayes (NB), and Nearest Centroid (NC). …”
Get full text

CNN-ViT: A multi-feature learning based approach for driver drowsiness detection by Madduri Venkateswarlu, Venkata Rami Reddy Chirra

“…The proposed system was evaluated on two separate datasets, named Dataset-1 and Dataset-2. …”
Get full text

Towards Transparent Deep Learning in Medicine: Feature Contribution and Attention Mechanism-Based Explainability by Thanveer Shaik, Xiaohui Tao, Haoran Xie, Lin Li, Niall Higgins, Juan D. Velásquez

“…Attention weights and Shapley values were computed for each input feature to provide global and local explanations, offering insights into the models’ behavior and feature importance. …”
Get full text

A correlation-based binary particle swarm optimization method for feature selection in human activity recognition by Huaijun Wang, Ruomeng Ke, Junhuai Li, Yang An, Kan Wang, Lei Yu

Get full text

A novel robust network construction and analysis workflow for mining infant microbiota relationships by Wei Jiang, Yue Zhai, Dongbo Chen, Qinghua Yu

“…However, consistency and solid workflows to construct and evaluate the process of network analysis are lacking. …”
Get full text

A generative adversarial network-based accurate masked face recognition model using dual scale adaptive efficient attention network by Jafar A. Alzubi, Kiran Sree Pokkuluri, Rajesh Arunachalam, Surendra Kumar Shukla, Sumanth Venugopal, Karthikayen Arunachalam

“…If the input images contain both masked and mask-free images, then it is directly given to Dual Scale Adaptive Efficient Attention Network (DS-AEAN). Otherwise, generated feature set 1 and feature set 2 are given to the DS-AEAN for recognizing the faces to ensure the person’s identity. …”
Get full text

Minimum uncertainty as Bayesian network model selection principle by Grigoriy Gogoshin, Andrei S. Rodin

“…Abstract Background Bayesian Network (BN) modeling is a prominent methodology in computational systems biology. …”
Get full text

Capsule neural network and its applications in drug discovery by Yiwei Wang, Binyou Wang, Jun Zou, Anguo Wu, Yuan Liu, Ying Wan, Jiesi Luo, Jianming Wu

Get full text

ConBGAT: a novel model combining convolutional neural networks, transformer and graph attention network for information extraction from scanned image by Duy Ho Vo Hoang, Huy Vo Quoc, Bui Thanh Hung

“…In this study, we introduce ConBGAT, a cutting-edge model that seamlessly integrates convolutional neural networks (CNNs), Transformers, and graph attention networks to address these shortcomings. …”
Get full text

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

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

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

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