Deep context-attentive transformer transfer learning for financial forecasting by Ling Feng, Ananta Sinchai

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A Highly Robust Encoder–Decoder Network with Multi-Scale Feature Enhancement and Attention Gate for the Reduction of Mixed Gaussian and Salt-and-Pepper Noise in Digital Images by Milan Tripathi, Waree Kongprawechnon, Toshiaki Kondo

“…HREDN integrates a multi-scale feature enhancement block in the encoder, allowing the network to capture features at various scales and handle complex noise patterns more effectively. …”
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MPFM-VC: A Voice Conversion Algorithm Based on Multi-Dimensional Perception Flow Matching by Yanze Wang, Xuming Han, Shuai Lv, Ting Zhou, Yali Chu

“…Voice conversion (VC) is an advanced technology that enables the transformation of raw speech into high-quality audio resembling the target speaker’s voice while preserving the original linguistic content and prosodic patterns. In this study, we propose a voice conversion algorithm, Multi-Dimensional Perception Flow Matching (MPFM-VC). …”
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Leveraging Radiomics and Genetic Algorithms to Improve Lung Infection Diagnosis in X-Ray Images Using Machine Learning by A. Beena Godbin, S. Graceline Jasmine

“…Radiomics, an emerging discipline in medical imaging, focuses on extracting detailed quantitative features from images to unveil subtle patterns imperceptible to the naked eye. …”
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Improving the prediction of streamflow in large watersheds based on seasonal trend decomposition and vectorized deep learning models by Ningchang Kang, Zhaocai Wang, Anbin Zhang, Hang Chen

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Gait Phase Recognition in Multi-Task Scenarios Based on sEMG Signals by Xin Shi, Xiaheng Zhang, Pengjie Qin, Liangwen Huang, Yaqin Zhu, Zixiang Yang

“…However, due to the similarity in muscle activation patterns between adjacent gait phases, the recognition accuracy is often low, which can easily lead to confusion in surface electromyography (sEMG) feature extraction. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

“…The input video from the dataset has been transformed to frames through median filtering. Next, feature extraction is applied to a preprocessed image, resulting in the fusion of sensor data. …”
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Enhancing Emergency Response in Road Accidents: A Severity Prediction Framework Using RF-RFE and Deep Learning Model by Chaimaa Chaoura, Hajar Lazar, Zahi Jarir

“…The dataset is refined using Random Forest Recursive Feature Elimination (RF-RFE) to select key features influencing accident severity. …”
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Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

“…Conventional image recognition algorithms exhibit limitations in processing barefoot footprint images characterized by concentrated feature distributions and rich texture patterns. To address this, our framework integrates an improved StarNet into the backbone of YOLOv8 architecture. …”
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Lightweight hybrid transformers-based dyslexia detection using cross-modality data by Abdul Rahaman Wahab Sait, Yazeed Alkhurayyif

“…A multi-modal attention-based feature fusion network was used to fuse the extracted features in order to guarantee the integration of key multi-modal features. …”
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Enhancing Cybersecurity Through Fusion of Optimization With Deep Wavelet Neural Networks on Denial of Wallet Attack Detection in Serverless Computing by P. Renukadevi, Sibi Amaran, A. Vikram, T. Prabhakara Rao, Mohamad Khairi Ishak

“…This attack is mainly associated with serverless frameworks due to features like auto-scaling, cost amplification, pay-as-you-go, and limited control. …”
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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…Furthermore, the binary olympiad optimization algorithm (BOOA)-based feature selection is utilized to extract the most informative features, reducing the data dimensionality. …”
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Importance of Spectral Information, Seasonality, and Topography on Land Cover Classification of Tropical Land Cover Mapping by Chansopheaktra Sovann, Stefan Olin, Ali Mansourian, Sakada Sakhoeun, Sovann Prey, Sothea Kok, Torbern Tagesson

“…Accurate land cover (LC) mapping is vital to monitor these changes, but mapping tropical forests is challenging due to complex spatial patterns, spectral similarities, and frequent cloud cover. …”
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A Synergy Between Machine Learning and Formal Concept Analysis for Crowd Detection by Anas M. Al-Oraiqat, Oleksandr Drieiev, Sattam Almatarneh, Mohammadnoor Injadat, Karim A. Al-Oraiqat, Hanna Drieieva, Yassin M. Y. Hasan

“…Recent systems take advantage of the synergy between machine learning, data mining, and image processing to extract/analyze features from crowded zones and recognize patterns and anomalies from the crowd behavior. …”
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A Diffusion–Attention-Enhanced Temporal (DATE-TM) Model: A Multi-Feature-Driven Model for Very-Short-Term Household Load Forecasting by Yitao Zhao, Jiahao Li, Chuanxu Chen, Quansheng Guan

“…Thus, we propose a diffusion–attention-enhanced temporal (DATE-TM) model with multi-feature fusion to address the above issues. First, the DATE-TM model could integrate residents’ electricity consumption patterns with climatic factors. …”
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Combining 2D texture and 3D geometry features for Reliable iris presentation attack detection using light field focal stack by Zhengquan Luo, Yunlong Wang, Nianfeng Liu, Zilei Wang

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Prevalence and spectrum of PIK3 mutations in breast cancer and their correlation with clinicopathological features: A cross-sectional observational study from South India by HS Darling, Rahul Sud, Deep Kumar Raman

“…The secondary objectives included evaluating the correlation of PIK3CA mutations with clinicopathological features such as tumor grade, stage, receptor status, molecular subtype, and metastatic pattern. …”
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Epidemiologic, Clinical, Ultrasonographic, and Cytological Features of Thyroid Nodules in Predicting Malignancy Risk: A Retrospective Study of 442 French Afro-Caribbean Patients by Johan Joseph-Auguste, Lucien Lin, Magalie Demar, Olivier Duffas, Vincent Molinie, Caroline Sulpicy, Marie-Josée Dorival, Olivier Luxembourger, Nadia Sabbah

“…Hypoechogenicity in solid pattern nodules and nodules between 2 and 3 cm in size revealed a high diagnostic value in detecting malignancy. …”
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Epidemic situation and features of accompanying therapy in the treatment of socially significant infectious diseases in penitentiary populations before, during, and after the COVID... by V. M. Kolomiets, N. A. Polshikova, A. Yu. Petrov, A. L. Kovalenko, E. V. Talikova

“…The second stage of the study was the analysis of data on tuberculosis (TB): features of the clinical course, etiotropic treatment, and the possibility of increasing efficiency through accompanying therapy.Results. …”
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A two-stage model for enhanced mango leaf disease detection using an innovative handcrafted spatial feature extraction method and knowledge distillation process by Mohammad Manzurul Islam, Mst. Nasrat Jahan Niva, Abdullahi Chowdhury, Saleh Masum, Rifat Ara Shams, Taskeed Jabid, Md. Sawkat Ali, Md. Mostofa Kamal Rasel, Muhammad Firoz Mridha

“…In the first stage, we implement an innovative, block-based feature extraction technique using Local Directional Patterns (LDP) and Local Directional Pattern variance (LDPv) on a comprehensive dataset, MangoLeafBD, consisting of 4000 images, achieving satisfactory results in terms of detection accuracy, sensitivity, specificity, and false negative rate. …”
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