Large Pretrained Foundation Model for Key Performance Indicator Multivariate Time Series Anomaly Detection by Xu Wang, Qisheng Xu, Kele Xu, Ting Yu, Bo Ding, Dawei Feng, Yong Dou

“…Furthermore, to address the multivariate challenge, we introduce a novel feature extraction method based on channel independence to optimize information processing across multidimensional features. …”
Get full text

BRA-YOLOv10: UAV Small Target Detection Based on YOLOv10 by Quanyu Zhang, Xin Wang, Heng Shi, Kunhui Wang, Yan Tian, Zhaohui Xu, Yongkang Zhang, Gaoxiang Jia

“…Firstly, Bi-Level Routing Attention (BRA) is used during the feature extraction stage to effectively reduce background interference. …”
Get full text

Multimodal depression detection based on an attention graph convolution and transformer by Xiaowen Jia, Jingxia Chen, Kexin Liu, Qian Wang, Jialing He

“…Traditional depression detection methods typically rely on single-modal data, but these approaches are limited by individual differences, noise interference, and emotional fluctuations. To address the low accuracy in single-modal depression detection and the poor fusion of multimodal features from electroencephalogram (EEG) and speech signals, we have proposed a multimodal depression detection model based on EEG and speech signals, named the multi-head attention-GCN_ViT (MHA-GCN_ViT). …”
Get full text

Development of an Optimized Two-Step Solid-Phase Extraction Method for Urinary Nucleic Acid Adductomics by Alexandra Keidel, Jazmine Virzi, Laura Deloso, Carolina Möller, Dale Chaput, Theresa Evans-Nguyen, Yuan-Jhe Chang, Mu-Rong Chao, Chiung-Wen Hu, Marcus S. Cooke

“…Using our approach, FeatureHunter 1.3 recognized approximately 500 adducts in both mouse and human urine samples. …”
Get full text

Cross-Modality Consistency Network for Remote Sensing Text-Image Retrieval by Yuchen Sha, Yujian Feng, Miao He, Yichi Jin, Shuai You, Yimu Ji, Fei Wu, Shangdong Liu, Shaoshuai Che

“…Second, CFM is designed to estimate co-occurrence probability by measuring fine-grained feature similarity, thereby reinforcing the relations of target-consist features across modalities. …”
Get full text

MSMT-RTDETR: A Multi-Scale Model for Detecting Maize Tassels in UAV Images with Complex Field Backgrounds by Zhenbin Zhu, Zhankai Gao, Jiajun Zhuang, Dongchen Huang, Guogang Huang, Hansheng Wang, Jiawei Pei, Jingjing Zheng, Changyu Liu

“…The Faster-RPE Block is first designed to enhance multi-scale feature extraction while reducing model Params and FLOPs. …”
Get full text

A Joint Moving Target Detection Method in Video SAR Via Low-Rank Sparse Decomposition and Transformer by Hui Fang, Guisheng Liao, Yongjun Liu, Cao Zeng, Xiongpeng He, Mingming Xu

“…Then, we improve faster RCNN and build a two-stream extraction feature network based on the Transformer structure that allows the video SAR image and the sparse image as input simultaneously as well as extracts and fuses the features from two types of the images, which can acquire more discriminative target features, thereby improving the final the detection performance. …”
Get full text

Exploring the application of knowledge transfer to sports video data by Shahrokh Heidari, Gibran Zazueta, Riki Mitchell, David Arturo Soriano Valdez, Mitchell Rogers, Mitchell Rogers, Jiaxuan Wang, Ruigeng Wang, Marcel Noronha, Alfonso Gastelum Strozzi, Mengjie Zhang, Patrice Jean Delmas, Patrice Jean Delmas

“…We focus on ZSL and player re-identification models that use feature embeddings to measure similarity between players. …”
Get full text

Attention residual network for medical ultrasound image segmentation by Honghua Liu, Peiqin Zhang, Jiamin Hu, Yini Huang, Shanshan Zuo, Lu Li, Mailan Liu, Chang She

“…Moreover, due to the significant noise present in ultrasound images, the model is prone to interference. In this research, we propose an Attention Residual Network model (ARU-Net). …”
Get full text

ENHANCEMENT OF CODE DIVISION MULTIPLE ACCESS (CDMA) WITHIN THE GSM SYSTEM IN IRAQ by Nabil Abdulwahab Abdulrazaq Baban

“…CDMA is particularly well-suited for the GSM system in Iraq due to its inherent advantages in handling interference and managing spectrum efficiently. Unlike TDMA, FDMA, which are primarily used in GSM in Iraq, CDMA spreads the signal across a wide frequency band, making it more resilient to interference. …”
Get full text

Ultrashort wave satellite channel classification and recognition algorithm based on mirror filled spectrum and LA-ResNet50 by Shang WU, Lei SHEN, Lijun WANG, Ruxu ZHANG, Xin HU

“…In response to the classification and identification problems of 5 kHz channels, 25 kHz channels, broadband interference channels, narrowband interference channels, and single tone interference channels in the ultrashort wave frequency band, a classification and identification method for ultrashort wave channels based on mirror filled spectrum and LA-ResNet50 (LBP attention ResNet50) was proposed.The problem of difficulty in distinguishing between satellite channels and background noise under low signal-to-noise ratio, as well as the identification of signal channels and interference channels with similar characteristics, has been effectively solved.Firstly, the proposed method performs mirror symmetry on the ultrashort wave spectrum and fills it in, while blackening the edges of the spectrum to construct a mirror-filled spectrum, which improves the discrimination of different types of channel spectra.Then, channel attention was introduced into ResNet50 to focus the attention of the network model on the channel.Finally, a loss function based on cross entropy and local binary pattern (LBP) was proposed to improve the extraction effect of subtle texture features on signal channels and interference channels images.The proposed method based on mirror-filled spectrum and LA-ResNet50 has shown an improvement of 19.8%, 8.2%, 1.8%, and 0.8% in classification accuracy for ultrashort wave channels compared to the traditional method utilizing fast Fourier transform (FFT) spectrum thresholding, the YOLOv5s target detection and classification method based on mirror-filled spectrum, the Attention-ResNet50 method with attention mechanism based on mirror-filled spectrum, and the Transformer network method under a signal-to-noise ratio (SNR) of 10 dB.…”
Get full text

A Detection Method for Open–Close States of High-Voltage Disconnector in Smoky Environments by Lujia Wang, Yifan Chen, Jianghao Qi, Kai Zhou, Zhijie He, Lei Jin

“…This paper delves into the impact of a smoky environment on point cloud data and introduces a two-stage discrimination process. Firstly, a feature extraction method using sliced point clouds is employed to construct edge features of the conductive arm. …”
Get full text

Hybrid machine learning-based 3-dimensional UAV node localization for UAV-assisted wireless networks by Workeneh Geleta Negassa, Demissie J. Gelmecha, Ram Sewak Singh, Davinder Singh Rathee

“…The proposed model efficiently managed interference, adapted to UAV mobility, and ensured optimal throughput by dynamically optimizing UAV trajectories. …”
Get full text

Quality Control Charts for EWMA with Wavelet Shrinkage: A Simulation Study by Esraa Haydier, Dlshad Saleh, Taha Ali, Bekhal Sedeeq

“…However, weight measurements are frequently susceptible to noise and interference due to factors such as measurement errors or natural variations. …”
Get full text

Recognition of common shortwave protocols and their subcarrier modulations based on multi-scale convolutional GRU. by Jiuxiao Cao, Rui Zhu, Zhen Wang, Jun Wang, Guohao Shi, Peng Chu

“…This hybrid architecture enhances both spatial feature diversity and sequential learning capacity. …”
Get full text

MF-YOLOv10: Research on the Improved YOLOv10 Intelligent Identification Algorithm for Goods by Quanwei Wang, Xiaoyang Wang, Jiayi Hou, Xuying Liu, Hao Wen, Ziya Ji

“…To enhance the accuracy of identifying parts and goods in automated loading and unloading machines, this study proposes a lightweight detection model, MF-YOLOv10, based on intelligent recognition of goods’ shape, color, position, and environmental interference. The algorithm significantly improves the feature extraction and detection capabilities by replacing the traditional IoU loss function with the MPDIoU and introducing the SCSA attention module. …”
Get full text

Tomato ripeness detection method based on FasterNet block and attention mechanism by Ming Chen, Yixuan Xu, Wanxiang Qin, Yan Li, Jiyang Yu

“…Traditional detection methods rely on manual experience, which is time-consuming, inefficient, and prone to subjective interference, making them unsuitable for large-scale production. …”
Get full text

Traditional guidance mechanism based deep robust watermarking by Xuejing GUO, Yixiang FANG, Yi ZHAO, Tianzhu ZHANG, Wenchao ZENG, Junxiang WANG

“…With the development of network and multimedia technology, multimedia data has gradually become a key source of information for people, making digital media the primary battlefield for copyright protection and anti-counterfeit traceability.Digital watermarking techniques have been widely studied and recognized as important tools for copyright protection.However, the robustness of conventional digital watermarking methods is limited as sensitive digital media can easily be affected by noise and external interference during transmission.Then the existing powerful digital watermarking technology’s comprehensive resistance to all forms of attacks must be enhanced.Moreover, the conventional robust digital watermarking algorithm’s generalizability across a variety of image types is limited due to its embedding method.Deep learning has been widely used in the development of robust digital watermarking systems due to its self-learning abilities.However, current initialization techniques based on deep neural networks rely on random parameters and features, resulting in low-quality model generation, lengthy training times, and potential convergence issues.To address these challenges, a deep robust digital watermarking algorithm based on a traditional bootstrapping mechanism was proposed.It combined the benefits of both traditional digital watermarking techniques and deep neural networks, taking into account their learning abilities and robust characteristics.The algorithm used the classic robust digital watermarking algorithm to make watermarked photos, and the constructed feature guaranteed the resilience of traditional watermarked images.The final dense image was produced by fusing the conventionally watermarked image with the deep network using the U-Net structure.The testing results demonstrate that the technique can increase the stego image’s resistance to various attacks and provide superior visual quality compared to the conventional algorithm.…”
Get full text

Reinforcement Learning-Based Television White Space Database by Armie E. Pakzad, Raine Mattheus Manuel, Jerrick Spencer Uy, Xavier Francis Asuncion, Joshua Vincent Ligayo, Lawrence Materum

“…The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. …”
Get full text

CBSNet: An Effective Method for Potato Leaf Disease Classification by Yongdong Chen, Wenfu Liu

“…Firstly, a convolution module called Channel Reconstruction Multi-Scale Convolution (CRMC) is designed to extract the upper and lower features by separating the channel features and applying a more optimized convolution to the upper and lower features, followed by a multi-scale convolution operation to capture the key changes more effectively. …”
Get full text