The abnormal audiovisual conflict in Parkinson’s disease patients is manifested in perception rather than response by Heng Zhou, Yiqing Bao, Nan Zou, Guohua Fan, Hanbin Sang, Erlei Wang, Aijun Wang

“…Furthermore, the cortical thickness of the left middle frontal gyrus (MFG) in PD patients was positively correlated with sensory interference (with visual interference > auditory interference) at period of perception. …”
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Resting Posture Recognition Method for Suckling Piglets Based on Piglet Posture Recognition (PPR)–You Only Look Once by Jinxin Chen, Luo Liu, Peng Li, Wen Yao, Mingxia Shen, Longshen Liu

“…This strengthens the model’s ability to capture and differentiate subtle posture features. Additionally, in the post-processing stage, the relative positions between sows and piglets are utilized to filter out piglets located outside the sow region, eliminating interference from sow nursing behaviors in resting posture recognition, thereby ensuring the accuracy of posture classification. …”
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Contrastive learning of cross-modal information enhancement for multimodal fake news detection by Weijie Chen, Fei Cai, Yupu Guo, Zhiqiang Pan, Wanyu Chen, Yijia Zhang

“…Thus, we construct an information enhancement and contrast learning framework by introducing Improved Low-rank Multimodal Fusion approach for Fake News Detection (ILMF-FND), which aims to reduce the noise interference and achieve efficient fusion of multimodal feature vectors with fewer parameters. …”
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Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8 by Tianxin Zhang, Fuwei Wang, Weimin Wang, Qihao Zhao, Weijun Ning, Haodong Wu

“…Secondly, an efficient multi-scale attention mechanism, EMA (Efficient Multi-Scale Attention Module), based on cross-space learning is integrated into the FPN (Feature Pyramid Network) part of the model. This mechanism highlights target features while suppressing background interference. …”
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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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Research on Citrus Leaf Disease Recognition Using Class-Agnostic Contrastive Learning and Supervised Organizational Mapping by Wen Xiao, Jinxia Shang, Fan Li, Ou Ao, Xin Wang, Shiyi Tian

“…Our key methodological innovations include a three-stage weakly supervised framework that systematically resolves background interference and feature redundancy: 1) Class-agnostic contrastive localization enabling precise lesion mapping without region annotations, 2) Stable feature initialization through region-guided classification training, 3) Sparse orthogonal mapping with experimentally-determined nodes introducing orthogonality constraints to enhance feature separation. …”
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U-MGA: A Multi-Module Unet Optimized with Multi-Scale Global Attention Mechanisms for Fine-Grained Segmentation of Cultivated Areas by Yun Chen, Yiheng Xie, Weiyuan Yao, Yu Zhang, Xinhong Wang, Yanli Yang, Lingli Tang

“…Specifically, a Multi-Scale Adaptive Segmentation (MSAS) is designed during the feature extraction phase to provide multi-scale and multi-feature information, supporting the model’s feature reconstruction stage. …”
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SIGKD: A Structured Instance Graph Distillation Method for Efficient Object Detection in Remote Sensing Images by Fangzhou Liu, Wenzhe Zhao, Haoxiang Qi, Guangyao Zhou

“…Through carefully calibrated weights, this strategy effectively extracts and integrates background information, thereby minimizing noise interference in detection results and augmenting the expressive capacity of foreground features. …”
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Fault Extraction of Wind Turbine Rolling Bearings Using FDEO and the Improved ACYCBD by Gong Yongli, Peng Dikang, Feng Tao, Liu Yibing

“…Finally, for the purpose of addressing the problem such as multiple vibration components existing in a vibration signal collected from wind turbines, which may mask the vibration component of interest, the improved ACYCBD is then used to extract the fault feature. The industrial results show that the proposed method is able to extract the faulty feature at an early stage without the interference of other vibration sources.…”
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Fault Diagnosis for Rolling Bearings Under Complex Working Conditions Based on Domain-Conditioned Adaptation by Xu Zhang, Gaoquan Gu

“…To address the issue of low diagnostic accuracy caused by noise interference and varying rotational speeds in rolling bearings, a fault diagnosis method based on domain-conditioned feature correction is proposed for rolling bearings under complex working conditions. …”
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Gear Fault Diagnosis Based on Empirical Mode Decomposition and 1.5 Dimension Spectrum by Jianhua Cai, Xiaoqin Li

“…The result shows that this method can greatly inhibit the interference of Gauss noise to raise the SNR and recognize the secondary phase coupling feature of the signal. …”
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Acquisition versus consolidation of auditory perceptual learning using mixed-training regimens. by David W Maidment, HiJee Kang, Emma C Gill, Sygal Amitay

“…Based on previous literature we predicted that acquisition would be disrupted by varying the task-relevant stimulus feature during training (stimulus interference), and that consolidation would be disrupted by varying the perceptual judgment required (task interference). …”
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Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using an Improved Particle Filter Algorithm Based on Cam-Shift Algorithm by Zhipeng Liu, Weipeng Guan, Shangsheng Wen

“…Experimental results show that the proposed algorithm has good accuracy, robustness and real-time performance under the environment of multiple interference factors. Accordingly, the proposed algorithm can be applied to the outdoor-VLC system with various environmental interferences, and can realize the actual first step of communication in VLC system based on image sensor well, laying a foundation for feature extraction, data transmission and other subsequent steps.…”
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Investigation of coplanar waveguide fed SWB antenna with controllable stop band characteristics by Ijaz Khan, Chaoyun Song, Habib Ullah, Xiaozhi Qi, Kuang Zhang, Salahuddin Khan, Yizhi Shao, Tao Gong, Mian Muhammad Kamal, Muhammad Sheraz, Teong Chee Chuah

“…The proposed antenna presents a compact and versatile solution for SWB applications, effectively mitigating interference from overlapping frequency bands. The reconfigurable notch feature, enabled by the varactor diode, provides a significant advantage over fixed-notch systems by allowing dynamic adjustment to different interference conditions. …”
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DAFDM: A Discerning Deep Learning Model for Active Fire Detection Based on Landsat-8 Imagery by Xu Gao, Wenzhong Shi, Min Zhang, Lukang Wang

“…Traditional methods for detecting AFs rely on the statistical analysis of AF radiance and background features. However, these algorithms are resource-intensive to develop and exhibit limited adaptability, particularly in distinguishing AF from interference pixels. …”
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EBBA-detector: An effective detector for defect detection in solar panel EL images with unbalanced data. by Yixing Zhang, Ziyan Mo, Zhuan Xin, Xianyu Chen, Yuqin Deng, Xuan Dong

“…The EBFPN captures defect features of different sizes, significantly improving the recognition ability for small defects, while the B-A Module suppresses background interference, guiding the model to focus more on defect locations. …”
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Defect Image Recognition and Classification for Eddy Current Testing of Titanium Plate Based on Convolutional Neural Network by Weiquan Deng, Jun Bao, Bo Ye

“…The structural characteristics of local connectivity and shared weights of CNN have better feature learning and characterization capabilities for titanium plate defect images under scan shift, scale distortion, and strong noise interference. …”
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Automatic LPI radar waveform recognition of overlapping signals based on vision language model by Pengkun Yang, Guangyi Li, Hui Tang, Yingjie Zhao, Hua Yan

“…By utilizing two distinct encoders for text and image, the model effectively aligns radar image and context prompt embeddings into a unified feature space. This alignment enables the model to more deeply learn and capture the intrinsic characteristics of radar waveforms, enhancing its ability to discern subtle modulation features. …”
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Research on Methods for the Recognition of Ship Lights and the Autonomous Determination of the Types of Approaching Vessels by Xiangyu Gao, Yuelin Zhao

“…Firstly, to address the challenges of the small target characteristics of ship lights and complex environmental interference, an improved YOLOv8 model is developed: The dilation-wise residual (DWR) module is introduced to optimize the feature extraction capability of the C2f structure. …”
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TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion by Lei He, Haijun Wei, Cunxun Sun

“…Secondly, we introduce the convolutional block attention module (CBAM) into the neck network to enhance salience for detecting wear particles while suppressing irrelevant information interference. Furthermore, multi-scale feature maps extracted by the backbone network are fed into the bidirectional feature pyramid network (BiFPN) for feature fusion to enhance the model’s ability to detect wear particle feature maps at different scales. …”
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