Parallel Net: Frequency-Decoupled Neural Network for DOA Estimation in Underwater Acoustic Detection by Zhikai Yang, Xinyu Zhang, Zailei Luo, Tongsheng Shen, Mengda Cui, Xionghui Li

“…The architecture adopts a frequency-parallel design: it first employs a recurrent neural network, the generalized feedback gated recurrent unit (GFGRU), to independently extract features from each frequency component, and then it fuses these features through an attention mechanism. …”
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ES-Net Empowers Forest Disturbance Monitoring: Edge–Semantic Collaborative Network for Canopy Gap Mapping by Yutong Wang, Zhang Zhang, Jisheng Xia, Fei Zhao, Pinliang Dong

“…First, a refined sample library containing multi-scale interference features was constructed, which included 2808 annotated UAV images. …”
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A Small Target Pedestrian Detection Model Based on Autonomous Driving by Yang Zhang, Shuaifeng Zhang, Dongrong Xin, Dewang Chen

“…To improve the accuracy of small-target pedestrian detection and the anti-interference ability of the model, a small-target pedestrian detection model that fuses residual networks and feature pyramids is proposed. …”
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Abstract model power field electromagnetic type building. Part 1 by Igor Pavlovich Popov

“…The formal model is an analogue of the electromagnetic field, not having these features in this model meets the essential requirements Ampere - unconditional implementation of Newton's third law.…”
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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

“…However, there are still several challenges to be tackled: its accuracy is often 2–3 m, it is prone to interference and attenuation effects, and the diversity of radio frequency receivers, for example, smartphones, affects its accuracy. …”
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GMTBLC: a deep learning-based bi-modal network traffic classification method by WEI Debin, JIANG Qinlong, WEN Jinglong, WANG Xinrui

“…In the data preprocessing phase, packet-level images within sessions were generated from the payloads of data packets to reduce information interference. In the classification phase, the images were firstly processed by the packet group mix transformer (PCMT) module, which utilized the transformer and GMA to capture global features. …”
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Investigating the Effectiveness of a Signal-based Approach in Improving Learners’ Decoding of Connected Speech The Case Study of Second-year Students, University of M’sila by Mohamed LAOUBI

“…It attempts to integrate CS instruction into the listening comprehension lessons following a diagnostic approach that uncovers CS features which may cause comprehension breakdown. An experimental group (N= 19) received listening lessons with an extended post-listening phase to address the CS features diagnosed as problematic during listening. …”
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Despot by Antranig Sarian

“…Iain Banks’ Complicity (1993) features a fictional ‘world-builder’ game called Despot that actively watches and emulates the player. …”
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Cloud Removal in Full-disk Solar Images Using Deep Learning by Zhenhong Shang, Peng Du, Zhenping Qiang, Runxin Li

“…Quantitative and qualitative experimental results demonstrate that the proposed method effectively removes complex cloud interference while preserving solar features, significantly improving the quality of observed data and outperforming existing solar image cloud removal methods. …”
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Denoising of electromagnetic data from different geological blocks using a hybrid PSO-GWO algorithm and CNN by Zhong-Yuan Liu, Zhong-Yuan Liu, Zhong-Yuan Liu, Di-Quan Li, Di-Quan Li, Di-Quan Li, Yecheng Liu, Yecheng Liu, Yecheng Liu, Xian Zhang, Xian Zhang, Xian Zhang

“…Noise interference remains a significant challenge in areas with high human activity, such as mining regions and urban environments. …”
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STDF: Joint Spatiotemporal Differences Based on xLSTM Dendritic Fusion Network for Remote Sensing Change Detection by Yu Zhou, Shengning Zhou, Dapeng Cheng, Jinjiang Li, Zhen Hua

“…In addition, we introduce a hierarchical dendritic coordination module based on the dendritic neuron model, which leverages a dynamic weighting mechanism to flexibly integrate multiscale feature maps. This approach not only mitigates the noise interference caused by traditional rigid fusion methods but also strengthens the separation of features between change regions and the background, thereby improving detection accuracy and model stability. …”
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Locating Building Change via Adaptive Frequency Enhancement by Lei Lu, Yuejie Li, Fei Yang, Haixiong Li, Guoqiang Wang, Kun Xie

“…It can adaptively enhance the information that favors the detection of architectural changes and suppresses irrelevant background noise interference. The entire network is designed with a classic U-shaped architecture, and two attention schemes are specifically designed, including spatial frequency attention module to regulate spatial-frequency weights in each level of feature maps, and the triple attention gate to comprehensively integrate spatial, channel, and frequency information. …”
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A Long-Tail Fault Diagnosis Method Based on a Coupled Time–Frequency Attention Transformer by Li Zhang, Ying Zhang, Hao Luo, Tongli Ren, Hongsheng Li

“…Furthermore, the model’s ability to fully learn features is enhanced through the linear coupling of time–frequency domain attention, which effectively mitigates noise interference and corrects imbalances in data distribution. …”
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A Deep Learning-Based Method for Object Workpiece Recognition and Grasp Detection by Yunhan Li, Jingjing Lou, Zhiduan Cai, Chuan Ye, Ruichao Zhao, Yuhang Jiang

“…To address this, this paper proposes a target object detection network (YOLO-Net) that integrates feature fusion and attention mechanisms. First, a deep learning-based object detection model is developed to effectively mitigate the interference caused by uneven lighting, accurately extracting the features of the target objects. …”
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Parameter-efficient adaptation with multi-channel adversarial training for far-field speech recognition by Tong Niu, Yaqi Chen, Dan Qu, Hengbo Hu, ChengRan Liu

“…This method uses fixed-length vector sequences appended to input features of each layer, enhancing the model’s capability for handling complex FSR tasks. …”
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USING RADIO FREQUENCY CURRENT TRANSFORMERS INSTEAD OF THE ROGOWSKI COILS IN HIGH VOLTAGE ROTATING EQUIPMENT by T.K. Nurubeyli, Z.K. Nurubayli, I.M. Ismayilov, G.N. Mammadova, A.R. Muslumzade

“…The study demonstrates that RFCTs offer significant advantages, including from high sensitivity to low-amplitude signals, resilience to radio interference, and a wide frequency bandwidth. These features make RFCTs particularly effective for use in environments with intense external interference, such as radar signals at industrial sites. …”
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Intelligent denoiser of plasma waves by SS-520-3 sounding rocket experiment toward future EMC challenges in miniaturized platform chassis by Mitsunori Ozaki, Ray Morita, Akihiro Hirano, Satoshi Yagitani, Yoshiya Kasahara, Takahiro Zushi, Satoshi Kurita, Hirotsugu Kojima

“…This sounding rocket experiment was aimed at improving our understanding of wave–particle interactions in the polar cusp. One key feature of the waveform clustering method is that it is based on an unsupervised machine learning technique, which relies solely on objective signal features and does not require subjective training data. …”
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Nigerian English and the Phonotactic Influence of the West Chadic Languages by Blessing Saina’an Lagan, Mary Daniel Nimram

“…This study examines the phonological constraints of four West Chadic languages in Nigeria (Piapung, Mwaghavul, Goemai and Kwagalak) and observes how the phonotactic features of these languages influence the English pronunciation of the native speakers by using the theory of Second Language Acquisition (SLA) and phonological interference or language transfer. …”
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CSI feedback algorithm for massive MIMO systems based on SFNet by ZHANG Yun, HUANG Jingwei, XU Sunwu, GAO Gui, YU Shujuan, ZHAO Shengmei

“…SFNet integrated a traditional convolutional neural network (CNN) and Transformer architecture, incorporating a spatial-frequency block designed to leverage global information and a multi-scale adaptive spatial attention gate for fusing local and global features. Fast Fourier convolution and a dynamic feature fusion mechanism were utilized to activate more input information, adjust the receptive field, selectively highlight spatially correlated features, suppress interference, and allow the network to achieve advanced performance with extremely low computational complexity. …”
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FAULT DIAGNOSIS METHOD OF ROLLING BEARING BASED ON ICEEMD-FastICA by MA WeiPing, HONG KunYue, AN Ning, SONG YuZhou

“…The maximum energy amplitude was obtained at the fault feature frequency, making it easy to identify fault features. …”
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