A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems by Chengxin Liu, Michele Ferlauto, Haiwen Yuan

“…The proposed method combines a self-attention mechanism with an adaptive graph convolutional neural network to enhance diagnostic precision. …”
Get full text

A Rolling-Bearing-Fault Diagnosis Method Based on a Dual Multi-Scale Mechanism Applicable to Noisy-Variable Operating Conditions by Jing Kang, Taiyong Wang, Ye Wei, Usman Haladu Garba, Ying Tian

“…Subsequently, we introduce the Dynamic Weighted Multi-Scale Feature Convolutional Neural Network (DWMFCNN) model, which integrates two structures: multi-scale feature extraction and dynamic weighting of these features. …”
Get full text

Investigating the accuracy of neural networks for blood pressure prediction in the ICU by Charles J. Gillan, Bartosz Gorecki

“…Two types of neural network are explored are explored in this paper: an encoder-decoder long short-term memory architecture and, separately, a convolutional neural network architecture. The top-performing configuration, when using a 70 %–30 % train-test split of data, is a convolutional neural network model. …”
Get full text

An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…This paper proposes a new fingerprint liveness detection method based on Siamese attention residual convolutional neural network (Res-CNN) that offers an interpretative perspective to this challenge. …”
Get full text

Application of Deep Learning in Forest Fire Prediction: A Systematic Review by Cesilia Mambile, Shubi Kaijage, Judith Leo

“…Key meteorological features, such as Temperature, Humidity, and Wind speed, have been extensively studied using the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and Normalized Difference Moisture Index (NDMI), the most commonly used satellite-derived features. …”
Get full text

Polarimetric SAR Ship Detection Using Context Aggregation Network Enhanced by Local and Edge Component Characteristics by Canbin Hu, Hongyun Chen, Xiaokun Sun, Fei Ma

“…Based on the characteristic differences of different scattering components in ships, this paper designs a context aggregation network enhanced by local and edge component characteristics to fully utilize the scattering information of polarized SAR data. …”
Get full text

Root Cause Analysis of Cast Product Defects with Two-Branch Reasoning Network Based on Continuous Casting Quality Knowledge Graph by Xiaojun Wu, Xinyi Wang, Yue She, Mengmeng Sun, Qi Gao

“…However, reasoning schemes for general KGs often use the same processing method to deal with different types of relations, without considering the difference in the number distribution of the head and tail entities in the relation, leading to a decrease in reasoning accuracy. …”
Get full text

CGD-CD: A Contrastive Learning-Guided Graph Diffusion Model for Change Detection in Remote Sensing Images by Yang Shang, Zicheng Lei, Keming Chen, Qianqian Li, Xinyu Zhao

“…Ultimately, high-quality difference images are generated from the extracted bi-temporal features, then use thresholding analysis to obtain a final change map. …”
Get full text

Drone-Based Digital Phenotyping to Evaluating Relative Maturity, Stand Count, and Plant Height in Dry Beans (Phaseolus vulgaris L.) by Leonardo Volpato, Evan M. Wright, Francisco E. Gomez

“…A time series of drone images was utilized to estimate dry bean RM employing a hybrid convolutional neural network (CNN) and long short-term memory (LSTM) model. …”
Get full text

ILR-Net: Low-light image enhancement network based on the combination of iterative learning mechanism and Retinex theory. by Mohan Yin, Jianbai Yang

“…In the adaptive learning sub-network, a dilated convolution module, U-Net feature extraction module, and adaptive iterative learning module are designed. …”
Get full text

DEFIF-Net: A lightweight dual-encoding feature interaction fusion network for medical image segmentation. by Zhanlin Ji, Shengnan Hao, Quanming Zhao, Zidong Yu, Hongjiu Liu, Lei Li, Ivan Ganchev

“…Additionally, a novel multi-branch ghost module (MBGM) is used in the bottleneck layer of the network to enhance its efficiency in capturing and retaining different types of feature information. Lastly, a novel residual feature enhancement (RFE) decoder is utilized to emphasize boundary features, thereby increasing the network's sensitivity to lesion boundaries. …”
Get full text

Evaluating the Impact of Frequency Decomposition Techniques on LSTM-Based Household Energy Consumption Forecasting by Maissa Taktak, Faouzi Derbel

“…Contemporary approaches like LSTM and GRU networks process raw time series directly, failing to distinguish between distinct frequency components that represent different physical phenomena in household energy usage. …”
Get full text

Review of One-Stage Universal Object Detection Algorithms in Deep Learning by WANG Ning, ZHI Min

“…This paper takes one-stage object detection as the starting point and analyzes and summarizes the mainstream one-stage detection algorithms of the first one-stage object detection algorithm YOLO series (YOLOv1 to YOLOv11, YOLO main improved version), SSD, and DETR series based on Transformer architecture, based on the use of two different architectures: classical convolution and Transformer. …”
Get full text

Research on unsupervised domain adaptive bearing fault diagnosis method by WU ShengKai, SHAO Xing, WANG CuiXiang, GAO Jun

“…Aiming at the problem that the bearing fault diagnosis algorithm based on deep learning has poor diagnosis performance when the fault samples are lack of labels in different working conditions and real environmentsly, an unsupervised domain adaptive bearing fault diagnosis method was proposed to realize the unsupervised fault diagnosis of bearings under different working conditions. …”
Get full text

Detection of Soluble Solid Content in Citrus Fruits Using Hyperspectral Imaging with Machine and Deep Learning: A Comparative Study of Two Citrus Cultivars by Yuxin Xiao, Yuanning Zhai, Lei Zhou, Yiming Yin, Hengnian Qi, Chu Zhang

“…Combined models that integrated different deep learning architectures were also explored. …”
Get full text

A New and Tested Ionospheric TEC Prediction Method Based on SegED-ConvLSTM by Yuanhang Liu, Yingkui Gong, Hao Zhang, Ziyue Hu, Guang Yang, Hong Yuan

“…We also examined the effect of using different numbers of space weather feature values in these models. …”
Get full text

Proposal of a Viscous Model for Nonviscously Damped Beams Based on Fractional Derivatives by Mario Lázaro, Jose M. Molines-Cano, Ignacio Ferrer, Vicente Albero

“…The theoretical results are contrasted with two different numerical examples.…”
Get full text

Improving High-Precision BDS-3 Satellite Orbit Prediction Using a Self-Attention-Enhanced Deep Learning Model by Shengda Xie, Jianwen Li, Jiawei Cai

“…SCINet-SA leverages deep learning to model the temporal characteristics of orbit differences between BDS-3 ultra-rapid and final products. …”
Get full text

A Deep Learning Method for Human Sleeping Pose Estimation with Millimeter Wave Radar by Zisheng Li, Ken Chen, Yaoqin Xie

“…To capture both frequency features and sequential features, we introduce ResTCN, an effective architecture combining Residual blocks and Temporal Convolution Network (TCN) to recognize different sleeping postures, from augmented statistical motion features of the radar time series. …”
Get full text

A Lightweight Model Enhancing Facial Expression Recognition with Spatial Bias and Cosine-Harmony Loss by Xuefeng Chen, Liangyu Huang

“…The LFN introduces combined channel operations and depth-wise convolution techniques, effectively reducing the number of parameters while enhancing feature representation capability. …”
Get full text