TSNetIQ: High-Resolution DOA Estimation of UAVs Using Microphone Arrays by Kequan Zhu, Tian Jin, Shitong Xie, Zixuan Liu, Jinlong Sun

“…This study offers superior accuracy and robustness for real-time sound source localization in UAV applications under dynamic scenarios.…”
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SiamAHG: adaptive hierarchical graph attention for lightweight siamese tracking by Na Li, Yaofu Fan, Xuhao Chen, Xinyu Liu, Jinglu He

“…AFMRM refines feature maps of different stages and strengthens the model expression by combining multiple convolutional kernels dynamically based upon diverse attentions. …”
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Evaluating the Performance of a Fake News Model on A Domain-Specific and Heterogeneous Dataset to Improve Detection by Georgina Obuandike, Emmy Danny Ajik, Faith Oluwatosin Echobu

“…These findings suggest that dynamic and robust fake news detection systems should integrate both heterogeneous datasets and domain-specific features to enhance effectiveness. …”
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A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES Penetrations by João Passagem dos Santos, Hugo Algarvio

“…This work uses machine learning techniques that dynamically compute it using the day-ahead programmed and expected dispatches of variable renewable energy sources, demand, and other technologies. …”
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Enhanced Location Prediction for Wargaming with Graph Neural Networks and Transformers by Dingge Liang, Junliang Li, Junping Yin

“…However, situational data provided by tactical wargame systems present significant challenges: high redundancy across consecutive frames and extreme data sparsity, with units occupying only a small fraction of the overall map. Traditional convolutional neural networks (CNNs) struggle to extract meaningful patterns from such data. …”
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A WiFi RSSI ranking fingerprint positioning system and its application to indoor activities of daily living recognition by Zixiang Ma, Bang Wu, Stefan Poslad

“…Second, Kendall tau correlation coefficient and a convolutional neural network are applied to extract the ranking features for estimating locations. …”
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G-KAN: Graph Kolmogorov-Arnold Network for Node Classification Using Contrastive Learning by Lining Yuan

“…Graph Convolutional Networks (GCN) and their variants utilize learnable weight matrices and nonlinear activation functions to extract features from data. …”
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A Hybrid Deep Learning-Based Load Forecasting Model for Logical Range by Hao Chen, Zheng Dang

“…In such environments, task-processing devices often experience highly dynamic workloads due to varying task demands, leading to scheduling inefficiencies and increased latency. …”
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Bearing fault diagnosis based on improved DenseNet for chemical equipment by Wu Huiyong, Jiang Kuan, Wang Yanyu

“…To enhance the model’s feature extraction capability, the CBAM (Convolutional Block Attention Module) is integrated into the Dense Block, dynamically adjusting channel and spatial attention to focus on crucial features. …”
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A machine learning model for the prediction of hail-affected area in Germany by Siyu Li, Peter Knippertz, Michael Kunz, Jannik Wilhelm, Julian Quinting

“…The ML model utilizes 18 thermodynamic and dynamic convection-related parameters derived from ERA5 reanalysis data. …”
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A small underwater object detection model with enhanced feature extraction and fusion by Tao Li, Yijin Gang, Sumin Li, Yizi Shang

“…Next, a variable kernel convolution (VKConv) is proposed to dynamically adjust the convolution kernel size, enabling better multi-scale feature extraction. …”
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A Survey of Deep Learning-Driven 3D Object Detection: Sensor Modalities, Technical Architectures, and Applications by Xiang Zhang, Hai Wang, Haoran Dong

“…Regarding technical architectures, the paper examines structured representation optimization in traditional convolutional networks, spatiotemporal modeling breakthroughs in bird’s-eye view (BEV) methods, voxel-level modeling advantages of occupancy networks for irregular objects, and dynamic scene understanding capabilities of temporal fusion architectures. …”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…The advantage of this approach lies in the model’s ability to learn and understand the dynamic behavior of the building from monitoring datasets. …”
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Towards efficient IoT communication for smart agriculture: A deep learning framework. by Ghada Alturif, Wafaa Saleh, Alaa A El-Bary, Radwa Ahmed Osman

“…This paradigm change emphasizes the inherent link between precise achievable data rate and energy efficiency, resulting in resilient agricultural ecosystems capable of adjusting to dynamic environmental conditions for optimal crop output and health.…”
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Fault Diagnosis for Rolling Bearings Under Complex Working Conditions Based on Domain-Conditioned Adaptation by Xu Zhang, Gaoquan Gu

“…Subsequently, a domain-conditioned adaptation strategy is introduced to dynamically adjust the activation of self-calibrating convolution channels in response to the differences between source and target domain inputs, generating correction terms for target domain features to facilitate effective domain-specific knowledge extraction. …”
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Helium Speech Recognition Method Based on Spectrogram with Deep Learning by Yonghong Chen, Shibing Zhang, Dongmei Li

“…Then, we combine a deep fully convolutional neural network with connectionist temporal classification (CTC) to form an acoustic model, in which the spectrogram features of helium speech are used as an input to convert speech signals into phonetic sequences. …”
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A Reconfigurable Coarse-to-Fine Approach for the Execution of CNN Inference Models in Low-Power Edge Devices by Auangkun Rangsikunpum, Sam Amiri, Luciano Ost

“…Convolutional neural networks (CNNs) have evolved into essential components for a wide range of embedded applications due to their outstanding efficiency and performance. …”
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A digital twin framework with MobileNetV2 for damage detection in slab structures by Duong Huong Nguyen, Huan Nguyen, Xiaohong Gao

“…To verify the proposed framework, we present a case study of slab structure using deflection measurement as input data. The dynamic characteristics of the physical model are used to calibrate the digital twin model. …”
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Enhancing Tomato Detection in Complex Field Environments using Faster R-CNN Deep Learning Model for Autonomous Picking Robots by Pandey Devras, Lalmawipuii R.

“…However, accurately detecting tomatoes in dynamic and complex field environments remains a challenge due to issues such as high false positive rates, missed detections, variable illumination, occlusion, and heterogeneous foliage. …”
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Enhancing book genre classification with BERT and InceptionV3: a deep learning approach for libraries by Xinting Yang, Zehua Zhang

“…A scaled dot-product attention mechanism is used to effectively fuse these multimodal features, dynamically weighting their contributions based on contextual relevance. …”
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