Fault diagnosis of marine electric thruster gearbox based on MPDCNN under strong noisy environments by Qianming SHANG, Wanying JIANG, Yi ZHOU, Zhengqiang WANG, Yubo SUN

“…Meanwhile, a novel parallel dual-channel convolutional neural network structure is designed to explore both global features and deeper, finer details of the data, thereby enhancing the diagnostic performance of the method in strong noise environments.ResultsExperimental evaluation results under different noise conditions show that the proposed method achieves a fault diagnosis accuracy of over 98% in environments with strong noise. …”
Get full text

Multimodal Contrastive Learning for Remote Sensing Image Feature Extraction Based on Relaxed Positive Samples by Zhenshi Zhang, Qiujun Li, Wenxuan Jing, Guangjun He, Lili Zhu, Shijuan Gao

Get full text

CSSDet: small object detection via cross-scale feature enhancement on drone-view images by Gui Cheng, Qing Ding, Bowen Cai, Chaoya Dang, Yu Wang, Xiaolong Zuo, Zhenfeng Shao

“…CSSDet integrates an additional detection head for small objects and employs a bidirectional weighted feature pyramid network for effective cross-scale feature fusion, enhancing global perceptual capability. …”
Get full text

Advanced cloud intrusion detection framework using graph based features transformers and contrastive learning by Vijay Govindarajan, Junaid Hussain Muzamal

“…Network flows are modeled as graphs to capture relational patterns among IP addresses and services, and a Graph Neural Network (GNN) is used to extract structured embeddings. …”
Get full text

Research on deep learning model for stock prediction by integrating frequency domain and time series features by Wenjie Sun, Jianhua Mei, Shengrui Liu, Chunhong Yuan, Jiaxuan Zhao

“…The StockMixer with ATFNet model proposed in this paper integrates both time-domain and frequency-domain features. By fusing information from both domains, the deep neural network significantly improves prediction accuracy and reliability. …”
Get full text

Malware Detection and Classification in Android Application Using Simhash-Based Feature Extraction and Machine Learning by Wafaa Al-Kahla, Eyad Taqieddin, Ahmed S. Shatnawi, Rami Al-Ouran

Get full text

Revolutionizing classification: A novel gray level co-occurrence matrix and statistical feature-based segmentation approach by Abdelwahed Motwakel

Get full text

EEG-based schizophrenia diagnosis using deep learning with multi-scale and adaptive feature selection by Alanoud Al Mazroa, Majdy M. Eltahir, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K, Jaehyuk Cho

“…For classification purposes, AWFM enables our model to modify the importance of features dynamically. We evaluated our technique using a publicly available dataset of EEG recordings acquired from patients who have schizophrenia and everyday individuals. …”
Get full text

Leveraging spatial dependencies and multi-scale features for automated knee injury detection on MRI diagnosis by Jianhua Sun, Ye Cao, Ying Zhou, Baoqiao Qi

“…The research aims to provide an efficient and reliable tool for clinicians to aid in the diagnosis of knee joint disorders, particularly focusing on Anterior Cruciate Ligament (ACL) tears.MethodsKneeXNet leverages the power of graph convolutional networks (GCNs) to capture the intricate spatial dependencies and hierarchical features in knee MRI scans. …”
Get full text

Influence of slaughter age on meat quality, metabolite and volatile organic compound changes in Lueyang black-bone chickens by Jie Gao, Ning Chen, Jia Cheng, Zhengnan Yuan, Wenxian Zeng, Hongzhao Lu, Tao Zhang, Ling Wang

Get full text

Pillar-X: Integrating Self-Learned Image Features to Improve 3D Object Detection by Mihaly Csontho, Andras Rovid

“…This paper presents Pillar-X, a 3D object recognition framework designed to generate and use self-learned image features. Unlike approaches that rely on pre-trained networks, Pillar-X efficiently learns and fuses features from an image directly within an end-to-end pipeline. …”
Get full text

Neural network pruning based on channel attention mechanism by Jianqiang Hu, Yang Liu, Keshou Wu

“…However, most of the existing methods ignore the differences in the contributions of the output feature maps. In response to the above, we propose a novel neural network pruning method based on the channel attention mechanism. …”
Get full text

Spatial-spectral collaborative attention network for hyperspectral unmixing by Xiaojie Chen, Fanlei Meng, Ye Mo, Haixin Sun

“…In recent years, the transformer architecture has demonstrated exceptional feature extraction capabilities in the field of computer vision (CV). …”
Get full text

Virtual sample based techniques using deep features for SSPP face recognition in unconstrained environment. by Muhammad Tariq Siddique, Ibrahim Venkat, Humera Farooq, Sharul Tajuddin, S H Shah Newaz

“…A local region-based technique was proposed to deal with occlusion by creating virtual samples. A deep neural network-based model, FaceNet, was used to extract the features and a support vector machine was used for classification. …”
Get full text

Lightweight Blockchain for Data Integrity and Traceability in IoT Networks by Laura Garcia, Carlos Cancimance, Rafael Asorey-Cacheda, Claudia-Liliana Zuniga-Canon, Antonio-Javier Garcia-Sanchez, Joan Garcia-Haro

“…In this paper, we propose a lightweight blockchain for data integrity and traceability in IoT networks that adapts the Distributed Ledger Technology (DLT) feature of blockchain to the LoRaWAN wireless communication protocol. …”
Get full text

A Novel Method for Community Detection in Bipartite Networks by Ali Khosrozadeh, Ali Movaghar, Mohammad Mehdi Gilanian Sadeghi, Hamidreza Mahyar

“…The community structure is a major feature of bipartite networks, which serve as a typical model for empirical networks consisting of two kinds of nodes. …”
Get full text

Sensitivity of Spiking Neural Networks Due to Input Perturbation by Haoran Zhu, Xiaoqin Zeng, Yang Zou, Jinfeng Zhou

“…However, existing methods fall short in evaluating the sensitivity of SNNs featuring biologically plausible leaky integrate-and-fire (LIF) neurons due to the intricate neuronal dynamics during the feedforward process. …”
Get full text

Dual-Path Adversarial Denoising Network Based on UNet by Jinchi Yu, Yu Zhou, Mingchen Sun, Dadong Wang

Get full text

Binarized Neural Networks for Resource-Efficient Spike Sorting by Luca M. Meyer, Majid Zamani, Andreas Demosthenous

“…The novelty of this work resides in the developed network architecture. In comparison to previous research, this work presents a deep binarized neural network featuring two hidden layers, each containing 256 units to effectively capture the spike characteristics of complex neural data. …”
Get full text

Att-BEVFusion: An Object Detection Algorithm for Camera and LiDAR Fusion Under BEV Features by Peicheng Shi, Mengru Zhou, Xinlong Dong, Aixi Yang

“…Then, a channel attention mechanism is introduced to design a BEV feature fusion network to realize the fusion of camera BEV feature space and LiDAR BEV feature space. …”
Get full text