Precision-Driven Semantic Segmentation of Pipe Gallery Diseases Using PipeU-NetX: A Depthwise Separable Convolution Approach by Wenbin Song, Hanqian Wu, Chunlin Pu

Get full text

Vehicle detection method based on multi-layer selective feature for UAV aerial images by Yinbao Ma, Yuyu Meng, Jiuyuan Huo

Get full text

RSTHFS: A Rough Set Theory-Based Hybrid Feature Selection Method for Phishing Website Classification by Jahanggir Hossain Setu, Nabarun Halder, Ashraful Islam, M. Ashraful Amin

Get full text

Object detection model design for tiny road surface damage by Chenguang Wu, Min Ye, Hongwei Li, Jiale Zhang

“…Firstly, a backbone applied to road surface damage feature extraction is designed to solve the problems of feature loss and insufficient extraction of tiny damage during feature extraction. …”
Get full text

Early stroke behavior detection based on improved video masked autoencoders for potential patients by Meng Wang, Guanci Yang, Kexin Luo, Yang Li, Ling He

Get full text

A low illumination target detection method based on a dynamic gradient gain allocation strategy by Zhiqiang Li, Jian Xiang, Jiawen Duan

“…Additionally, the size of the improved detection head is reduced by adopting a parameter-sharing approach, thereby balancing detection accuracy with computational efficiency. …”
Get full text

Solar Flare Prediction Using Multivariate Time Series of Photospheric Magnetic Field Parameters: A Comparative Analysis of Vector, Time Series, and Graph Data Representations by Onur Vural, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi

Get full text

LN-DETR: cross-scale feature fusion and re-weighting for lung nodule detection by Dibin Zhou, Honggang Xu, Wenhao Liu, Fuchang Liu

“…First, we designed a Deep and Shallow Detail Fusion layer that effectively fuses cross-scale features from both shallow and deep layers. Second, we optimized the computational load of the backbone network, effectively reducing the overall scale of the model. …”
Get full text

Enhanced ResNet-50 for garbage classification: Feature fusion and depth-separable convolutions. by Lingbo Li, Runpu Wang, Miaojie Zou, Fusen Guo, Yuheng Ren

“…At the same time, the module filters out redundant information from multi-scale features, reducing the number of model parameters. …”
Get full text

A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…A dilation-wise residual module further optimizes multi-scale feature extraction. Evaluated on benchmark datasets, LightFAD-YOLO achieves 1.7 % higher mAP0.5 and 6.4 % improved mAP0.5:0.95 over baseline models, with 9.9 % lower computational load. …”
Get full text

EFINet: Efficient Feature Interaction Network for Real-Time RGB-D Semantic Segmentation by Zhe Yang, Baozhong Mu, Mingxun Wang, Xin Wang, Jie Xu, Baolu Yang, Cheng Yang, Hong Li, Rongqi Lv

“…Currently, although convolutional neural network (CNN) methods are less accurate than Transformer-based methods, they offer stronger real-time performance under the same computational load. Therefore, in this study, we proposed the Efficient Feature Interaction Network (EFINet), a real-time RGB-D segmentation method that uses a lightweight CNN encoder and incorporates encoder blocks with a lightweight upsampling method Dysample and the carefully optimized number of ConvNeXt V2 blocks, to redesign the decoder and minimize redundant computations. …”
Get full text

Efficient Attention Transformer Network With Self-Similarity Feature Enhancement for Hyperspectral Image Classification by Yuyang Wang, Zhenqiu Shu, Zhengtao Yu

“…Then, we embed these two self-similarity descriptors into the original patch for subsequent feature extraction and classification. Furthermore, we design two efficient feature extraction modules based on the preprocessed patches, called spectral interactive transformer module and spatial conv-attention module, to reduce the computational costs of the classification framework. …”
Get full text

Improved RT-DETR for Infrared Ship Detection Based on Multi-Attention and Feature Fusion by Chun Liu, Yuanliang Zhang, Jingfu Shen, Feiyue Liu

“…The experimental results show that, although the enhanced RT-DETR algorithm still experiences missed detections under severe object occlusion, it has significantly improved overall performance, including a 1.7% increase in mAP, a reduction in 4.3 M parameters, and a 5.8 GFLOPs decrease in computational complexity. …”
Get full text

A Lightweight Network for UAV Multi-Scale Feature Fusion-Based Object Detection by Sheng Deng, Yaping Wan

“…This approach introduces a new module, C2f_SEPConv, which incorporates Partial Convolution (PConv) and channel attention mechanisms (Squeeze-and-Excitation, SE), effectively replacing the previous bottleneck and minimizing both the model’s parameter count and computational demands. Modifications to the detection head allow it to perform more effectively in scenarios with small targets in aerial images. …”
Get full text

Development of Self-Powered Energy-Harvesting Electronic Module and Signal-Processing Framework for Wearable Healthcare Applications by Jegan Rajendran, Nimi Wilson Sukumari, P. Subha Hency Jose, Manikandan Rajendran, Manob Jyoti Saikia

Get full text

Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…Moreover, to augment the efficiency of feature integration and diminish computational demands, a novel fusion network combining SlimNeck with BiFPN-Concat was introduced, effectively merging superficial spatial details with profound semantic features. …”
Get full text

MSFE-Net: Multi-Scale Feature Enhancement Network for Remote Sensing Object Detection by Kai Yuan, Xing Li, Yaoyao Ren, Lianpeng Zhang, Wei Liu, Erzhu Li

“…Compared to other models, MSFE-Net balances between parameter counts and computational demand, with Params slightly higher than YOLOv5s and YOLOv7-tiny and GFLOPs in a moderately high range. …”
Get full text

A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…To address the current issue of large computations and the difficulty in balancing model complexity and detection accuracy in pavement defect detection models, a lightweight pavement defect detection algorithm, PGS-YOLO, is proposed based on YOLOv8, which integrates perception enhancement and feature optimization. …”
Get full text

Key Technology of Communication Equipment Fingerprint Recognition Based on Intelligent Feature Extraction Algorithm by Meizhen Gao, Yunquan Li, Yetong Gao

“…The autoencoder feature and four kinds of integral bispectrum feature are analyzed and visualized. …”
Get full text

Improved ICP point cloud registration method based on feature point extraction and PCA by Ma Ran

Get full text