Enhancing Emotion Recognition in Speech Based on Self-Supervised Learning: Cross-Attention Fusion of Acoustic and Semantic Features by Bashar M. Deeb, Andrey V. Savchenko, Ilya Makarov

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Machine Learning based estimation of Chlorophyll and Flavonoid content in Bitter Leaf using Color and GLCM Texture Features by Retno Damayanti, Yusuf Hendrawan, Sandra Sandra

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Human Depth Sensors-Based Activity Recognition Using Spatiotemporal Features and Hidden Markov Model for Smart Environments by Ahmad Jalal, Shaharyar Kamal, Daijin Kim

“…Finally, these optimal features are trained and they recognized activity using hidden Markov model. …”
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Investigations on higher-order spherical harmonic input features for deep learning-based multiple speaker detection and localization by Nils Poschadel, Stephan Preihs, Jürgen Peissig

“…Different spherical harmonic (SH) input features such as the higher-order pseudointensity vector (HO-PIV), relative harmonic coefficients (RHCs), and the spatially-localized pseudointensity vector (SL-PIV), a feature proposed for the first time as an input feature for deep learning-based SDL, are examined using first- to fourth-order SH signals. …”
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Emo-SL Framework: Emoji Sentiment Lexicon Using Text-Based Features and Machine Learning for Sentiment Analysis by Manar Alfreihat, Omar Saad Almousa, Yahya Tashtoush, Anas AlSobeh, Khalid Mansour, Hazem Migdady

“…Emoji weighting is integrated with text-based feature extraction using lexicons to train classifiers on an Arabic tweet dataset. …”
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Extracting Features from Oblique Ground-Based Multispectral Images for Monitoring Cotton Physiological Response to Nitrogen Treatments by Vaishali Swaminathan, J. Alex Thomasson, Nithya Rajan, Robert G. Hardin

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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…A novel transformation of the VGG-19 model for feature engineering based on transfer learning is introduced, where spatial features extracted from coffee bean images are transformed into class prediction probabilities using LGBM. …”
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EPI-DynFusion: enhancer-promoter interaction prediction model based on sequence features and dynamic fusion mechanisms by Ao Zhang, Jianhua Jia, Mingwei Sun, Xin Wei

“…This model begins by encoding DNA sequences using pre-trained DNA embeddings and extracting local features through convolutional neural networks (CNNs). …”
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Functional Monitoring of Patients With Knee Osteoarthritis Based on Multidimensional Wearable Plantar Pressure Features: Cross-Sectional Study by Junan Xie, Shilin Li, Zhen Song, Lin Shu, Qing Zeng, Guozhi Huang, Yihuan Lin

“…The multidimensional gait features extracted from the data and physical characteristics were used to establish the KOA functional feature database for the plantar pressure measurement system. 40mFPWT and TUGT regression prediction models were trained using a series of mature machine learning algorithms. …”
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Analysis of Facial Areas to Identify CHD Risks Based on Facial Textures by Budi Sunarko, Agung Adi Firdaus, Yudha Andriano Rismawan, Anan Nugroho

“…This study aimed to develop and evaluate a machine learning model or diagnose CHD using facial texture features and to compare the performance across different facial regions to provide recommendations for improvement. …”
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Schizo-Net: A <italic>novel</italic> Schizophrenia Diagnosis Framework Using Late Fusion Multimodal Deep Learning on Electroencephalogram-Based Brain Connectivity Indices by Nitin Grover, Aviral Chharia, Rahul Upadhyay, Luca Longo

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Performance Evaluation of Artificial Neural Network Methods Based on Block Machine Learning Classification by Raya Hamdy, Mohammed Younis

“…This study proposes a block-by-block (5x5 chunks) segmentation method for semantic segmentation, which involves image dissection, feature extraction, and model training based on specific color and textural properties. …”
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Occlusion Vehicle Target Recognition Method Based on Component Model by Haorui Han, Hanshan Li

“…Due to the complexity and occlusion of various objects in the traffic scene, the accuracy of vehicle target recognition is poor. Therefore, based on the distribution features of vehicle components, this paper proposes a two-stage VSRS-VCFM net occlusion vehicle target recognition method. …”
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Cloth-Changing Person Re-Identification Based on the Backtracking Mechanism by Xuan Liu, Hua Han, Kaiyu Xu, Li Huang

“…During training, we use a clothes suppression loss function to reduce the model&#x2019;s reliance on clothing features, further improving robustness. …”
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Enhanced diagnosis of planetary gear train faults based on bispectrum and attention mechanism deep convolutional generative adversarial networks by Dalian Yang, Yang Zhang, Renjie Li, Hui Long, Changzheng Huang

“…Abstract Aiming at the problem of inaccurate fault diagnosis caused by limited fault samples and challenging feature extraction in helicopter planetary gear trains, this study proposes a fault diagnosis method based on Bispectrum and Attention Mechanism Deep Convolutional Generative Adversarial Networks (BAMDCGAN). …”
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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

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RETINA: Reconstruction-based pre-trained enhanced TransUNet for electron microscopy segmentation on the CEM500K dataset. by Cheng Xing, Ronald Xie, Gary D Bader

“…Current approaches usually use either convolutional or transformer-based neural networks for image feature extraction. …”
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On Explainability of Reinforcement Learning-Based Machine Learning Agents Trained with Proximal Policy Optimization That Utilizes Visual Sensor Data by Tomasz Hachaj, Marcin Piekarczyk

“…In this paper, we address the issues of the explainability of reinforcement learning-based machine learning agents trained with Proximal Policy Optimization (PPO) that utilizes visual sensor data. …”
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Modelling radiological features fusion and explainable AI in pneumonia detection: A graph- based deep learning and transformer approach by Pratham Kaushik, Eshika Jain, Vinay Kukreja, Shanmugasundaram Hariharan, Murugaperumal Krishnamoorthy, Vandana Ahuja, Abhishek Bhattacherjee, Rajesh Kumar Kaushal, Shih-Yu Chen

“…The research focuses on integrating U-Net for lung segmentation, graph-based feature representations, and transformer-based models to improve interpretability and diagnostic accuracy. …”
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Predicting tensile and fracture parameters in polypropylene-based nanocomposites using machine learning with sensitivity analysis and feature impact evaluation by Pouya Rajaee, Faramarz Ashenai Ghasemi, Amir Hossein Rabiee, Mohammad Fasihi, Behnam Kakeh, Alireza Sadeghi

“…The results also include an analysis of the impact of the key features on each mechanical property based on the sensitivity analysis.…”
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