Underwater Reverberation Suppression Using Wavelet Transform and Complementary Learning by Jiajie Liu, Qunfei Zhang, Xiaodong Cui, Chencong Tang, Zijun Pu

“…Reverberation is the primary interference of active detection. Therefore, the effective suppression of reverberation is a prerequisite for reliable signal processing. …”
Get full text

A fine‐grained image classification method based on information interaction by Shuo Zhu, Xukang Zhang, Yu Wang, Zongyang Wang, Jiahao Sun

“…Abstract To enhance the accuracy of fine‐grained image classification and address challenges such as excessive interference factors within the dataset, inadequate extraction of local key features, and insufficient channel semantic association, a dual‐branch information interaction model that integrates convolutional neural networks (CNN) with Vision Transformers is proposed. …”
Get full text

End-to-End Intelligent Fault Diagnosis of Transmission Bearings in Electric Vehicles Based on CNN by Yong Chen, Guangxin Li, Anhe Li, Bolin He

“…Environmental noise and transmission components can cause significant interference in vibration signals, rendering the extraction of bearing fault features challenging in service scenarios. …”
Get full text

Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Key challenges in mine rescue scenarios are identified: ① significant localization errors and limited effective detection range in thick, heterogeneous, and discontinuous media; ② weakened radar echoes and severe clutter interference under Non-Line-of-Sight (NLOS) conditions, leading to low-precision micro-motion target detection and large real-time errors for dynamic targets; ③ signal interference and occlusion effects among multiple targets degrading localization accuracy. …”
Get full text

DADNet: text detection of arbitrary shapes from drone perspective based on boundary adaptation by Jun Liu, Jianxun Zhang, Ting Tang, Shengyuan Wu

“…Using ResNet50 as the backbone network, we introduce the proposed Hybrid Text Attention Mechanism into the backbone network to enhance the perception of text regions in the feature extraction module. Additionally, we propose a Spatial Feature Fusion Module to adaptively fuse text features of different scales, thereby enhancing the model’s adaptability. …”
Get full text

DAM-Faster RCNN: few-shot defect detection method for wood based on dual attention mechanism by Xingyu Tong, Zhihong Liang, Mingming Qin, Fangrong Liu, Jiayu Yang, Hengjiang Xiao, Wei Dai

“…The model integrates cross-attention and spatial attention modules to enhance the expression of key region features, suppresses texture noise interference; the improved Wood-Region Proposal Network (WRPs) module utilizes feature mean pooling and cross-layer fusion strategies to significantly improve the quality and robustness of candidate box generation; in addition, the Wood-Feature Reconstruction Head (WFRH) module effectively enhances the adaptability to new classes and few-shot defects through multi-branch classification and weighted fusion mechanisms. …”
Get full text

Single Vector Hydrophone DOA Estimation: Leveraging Deep Learning with CNN-CBAM by Fanyu ZENG, Yaning HAN, Hongyuan YANG, Dapeng YANG, Fan ZHENG

“…By inputting the covariance matrix of the received signal into the neural network and integrating the CBAM module, this method enhances the model’s sensitivity to critical features. The CBAM module leverages channel and spatial attention mechanisms to adaptively focus on essential information, effectively suppressing noise interference and improving directional accuracy. …”
Get full text

Magnetically tunable 4 × 2 encoder utilizing Terfenol-D-embedded phononic crystal ring resonators by Ehsan Mehdizadeh Omrani, Fakhroddin Nazari

“…The encoder features an ultra-compact footprint of 125 × 10-6 m2, with four input waveguides and two output waveguides, each equipped with a pair of ring resonators. …”
Get full text

ED-Swin Transformer: A Cassava Disease Classification Model Integrated with UAV Images by Jing Zhang, Hao Zhou, Kunyu Liu, Yuguang Xu

“…Firstly, we introduced the EMAGE (Efficient Multi-Scale Attention with Grouping and Expansion) module, which integrates the global distribution features and local texture details of diseased leaves in drone imagery through a multi-scale grouped attention mechanism, effectively mitigating the interference of complex background noise on feature extraction. …”
Get full text

The staff ensuring of publishing houses of the Soviet Ukraine in 20th-30th of XX century by Valentyna Molotkina

“…The article deals with special features of staff ensuring of USSR's publishing houses in 20-30th of XX century. …”
Get full text

Discrete PID-Type Iterative Learning Control for Mobile Robot by Hongbin Wang, Jian Dong, Yueling Wang

“…This algorithm used discrete PID to filter rejection and restrained the influence of interference and noise on trajectory tracking, which made it more suitable for engineering application. …”
Get full text

Intelligent security relay selection for full duplex wireless communications by Fang LIU, Yajuan WANG, Zhengrong LAI, Yuan’an LIU

“…Full-duplex can double the spectrum efficiency theoretically.Thus it can further improve the spectrum efficiency when it is used in the relay systems.Considering the residual self-interference and signal-to-noise ratio,a problem was set to maximize the security capacity by selecting the optimal relay.This optimization problem was transformed into multi-classification problem.Thus a convolutional neural network (CNN)-based intelligent relay selection scheme was proposed.In the design of the classification model,the CNN was used to extract the spatial correlation of the channel,and the dimension of the convolution kernel was related to the number of relays.The pooling layer was not used to preserve the matrix characteristics of the input features.The simulation results show that the proposed CNN-based intelligent selection classification model has high classification accuracy,and can obtain the same security performance as the traditional exhaustive search scheme,and the real-time performance is significantly improved.…”
Get full text

Fine-Grained Identification of Benthic Diatom Scanning Electron Microscopy Images Using a Deep Learning Framework by Fengjuan Feng, Shuo Wang, Xueqing Zhang, Xiaoyao Fang, Yuyang Xu, Jianlei Liu

“…This mechanism allows the network to focus more on foreground features that are useful for the classification task while significantly reducing the interference of background noise. …”
Get full text

Improvement of Lithological Identification Under the Impact of Sparse Vegetation Cover with 1D Discrete Wavelet Transform for Gaofen-5 Hyperspectral Data by Senmiao Guo, Qigang Jiang

“…The results show that andesite spectra are the most susceptible to vegetation interference. Absorption features in the 2.0–2.4 μm wavelength range were identified as critical indicators for distinguishing lithologies from mixed spectra. …”
Get full text

MDIGCNet: Multidirectional Information-Guided Contextual Network for Infrared Small Target Detection by Luping Zhang, Junhai Luo, Yian Huang, Fengyi Wu, Xingye Cui, Zhenming Peng

“…Additionally, we designed a local-global feature fusion (LGFF) module incorporating an attention mechanism to merge shallow and deep features, thereby improving the efficiency of feature utilization within the model. …”
Get full text

Peculiarities of Forming the Methodology for Investigating Criminal Offenses against the Authority of State Agencies in the Law Enforcement Sphere by V. O. Gusieva

“…It has been established that the structure of methods of investigating criminal offenses against the authority of state agencies in the field of law enforcement activity should consist of the following elements: 1) forensic characteristics of criminal offenses against the authority of state agencies in the field of law enforcement activity; 2) circumstances to be established; 3) features of the beginning of criminal proceedings, typical investigative situations, algorithms of investigative (search) and procedural actions at the initial and subsequent stages of investigation; 4) specific features of tactics of conducting certain investigative (search), covert investigative (search) and procedural actions; 5) general features of using special knowledge; 6) specific features of forensic prevention of criminal offenses against the authority of state agencies in the field of law enforcement activity.…”
Get full text

Alertness assessment by optical stimulation-induced brainwave entrainment through machine learning classification by Yong Zhou, Yizhou Tan, Shasha Wang, Hanshu Cai, Ying Gu

“…The correlation between nine EEG features during the BWE and different alertness states were analyzed. …”
Get full text

HYBRID FIREFLY AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DESIGN OF NON-LINEAR CHANNEL EQUALIZER by Vundavalli Ravindra, Pradyumna Kumar Mohapatra, Ravi Narayan Panda, Saroja Kumar Rout

“…Higher exploitation and exploration capabilities, as well as an improved ability to escape from local minima, are features of the suggested training plan. Furthermore, we compare the features of FFPSO with the classical features of FF and PSO. …”
Get full text

A Novel Machine Learning Technique for Fault Detection of Pressure Sensor by Xiufang Zhou, Aidong Xu, Bingjun Yan, Mingxu Gang, Maowei Jiang, Ruiqi Li, Yue Sun, Zixuan Tang

“…This method innovatively integrates multi-scale time series decomposition algorithms with time-domain and frequency-domain feature extraction techniques. Initially, this dataset is decomposed into multi-scale time series to mitigate periodic component interference in diagnosis. …”
Get full text

Classification of first embryonic division stages of multiple Caenorhabditis species by deep learning by Dhruv Khatri, Prachi Negi, Chaitanya A. Athale

“…We find activation vectors of the CNNs of the sparse EvoCellNet correlate with spatial localization of intracellular features of multiple species, such as pro-nuclei, spindle, and spindle-poles. …”
Get full text