GhostConv+CA-YOLOv8n: a lightweight network for rice pest detection based on the aggregation of low-level features in real-world complex backgrounds by Fei Li, Yang Lu, Qiang Ma, Shuxin Yin, Rui Zhao

“…To overcome these limitations, this paper introduces GhostConv+CA-YOLOv8n, a lightweight object detection framework was proposed, which incorporates several innovative features: GhostConv replaces standard convolutional operations with computationally efficient ghost modules in the YOLOv8n’s backbone structure, reducing parameters by 40,458 while maintaining feature richness; a Context Aggregation (CA) module is applied after the large and medium-sized feature maps were output by the YOLOv8n’s neck structure. …”
Get full text

Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection by Sixu Guo, Jiyou Fei, Liying Wang, Hua Li, Xiaodong Liu

“…However, many existing methods face challenges such as high parameters, complex computation, slow inspection speed, and low accuracy. …”
Get full text

Barefoot Footprint Detection Algorithm Based on YOLOv8-StarNet by Yujie Shen, Xuemei Jiang, Yabin Zhao, Wenxin Xie

“…In the feature fusion part, a feature modulation block processes multi-scale features by synergistically combining global and local information, thereby reducing redundant computations and decreasing both parameter count and computational complexity to achieve model lightweighting. …”
Get full text

Multi-objective predictive control of cascaded H-bridge multilevel inverter based grid integrated PV based distributed generation system with improved power quality features by Avismit Dutta, Roshan Pradhan, Aurobinda Panda

Get full text

A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…Moreover, to conserve computational resources, a lightweight CED module was introduced to reduce parameters and conserve the computing resources of the UAV. …”
Get full text

Small target detection in coal mine underground based on improved RTDETR algorithm by Feng Tian, Cong Song, Xiaopei Liu

“…This decreased the number of network parameters and computation. By introducing Deformable Attention in the coding part of the RTDETR algorithm, the deformable feature of this attention mechanism is used to improve the network’s ability to extract effective image features. …”
Get full text

LPCF-YOLO: A YOLO-Based Lightweight Algorithm for Pedestrian Anomaly Detection with Parallel Cross-Fusion by Peiyi Jia, Hu Sheng, Shijie Jia

“…Additionally, an ADown module is introduced in the third layer to reduce the computational cost. In the neck network, a Lightweight High-level Screening Feature Pyramid Network (L-HSFPN) is designed to replace the PAFPN structure. …”
Get full text

PCLC-Net: Parallel Connected Lateral Chain Networks for Infrared Small Target Detection by Jielei Xu, Xinheng Han, Jiacheng Wang, Xiaoxue Feng, Zhenxu Li, Feng Pan

“…Given the widespread influence of U-Net and FPN network architectures on infrared small target detection tasks on existing models, these structures frequently incorporate a significant number of downsampling operations, thereby rendering the preservation of small target information and contextual interaction both challenging and computation-consuming. To tackle these challenges, we introduce a parallel connected lateral chain network (PCLC-Net), an innovative architecture in the domain of infrared small target detection, that preserves large-scale feature maps while minimizing downsampling operations. …”
Get full text

An Improved Small Target Detection Algorithm Based on YOLOv8s by G. Ma, C. Xu, Z. Xu, X. Song

“…First, the S_C2f_CAFM module is integrated into the feature extraction network, enabling the effective capture of fine-grained local features and broad contextual information, while simultaneously reducing model parameters and computational complexity. …”
Get full text

DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…Our system achieves superior results compared to existing models using a self-constructed smoking detection dataset, reducing computational complexity by 23.20% while trimming the model parameters by 33.95%. …”
Get full text

Enhancing Object Detection in Underground Mines: UCM-Net and Self-Supervised Pre-Training by Faguo Zhou, Junchao Zou, Rong Xue, Miao Yu, Xin Wang, Wenhui Xue, Shuyu Yao

“…We propose the ESFENet backbone network, incorporating a Global Response Normalization (GRN) module to enhance feature capture stability while employing depthwise separable convolutions and HGRNBlock modules to reduce parameter volume and computational complexity. …”
Get full text

A Novel Transformer-Based Multiscale Siamese Framework for High-Resolution Remote Sensing Change Detection by Liangjun Wang, Weitao Chen, Haoyi Wang, Zhengchao Chen

“…Notably, compared to that of five multiscale-based methods, our proposed TMSF achieves superior performance while requiring only half the number of parameters and computational cost. Thus, the proposed model demonstrates a marked advancement in remote sensing CD. …”
Get full text

Multimodal recurrence risk prediction model for HR+/HER2- early breast cancer following adjuvant chemo-endocrine therapy: integrating pathology image and clinicalpathological featu... by Xiaoyan Wu, Yiman Li, Jilong Chen, Jie Chen, Wenchuan Zhang, Xunxi Lu, Xiaorong Zhong, Min Zhu, Yuhao Yi, Hong Bu

Get full text

Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…In addition, the detection performance is superior to other traditional detection models under the condition of low parameter quantities and computational complexity. …”
Get full text

Underwater image enhancement via multiscale disentanglement strategy by Jiaquan Yan, Hao Hu, Yijian Wang, Muhammad Wasim Nawaz, Naveed Ur Rehman Junejo, Ente Guo, Huibin Feng

Get full text

Improved YOLOv8 Object Detection Method for Drone Aerial Images by Zhong Shuai, Wang Liping

“…The experimental results on the VisDrone2019 dataset show: compared with the YOLOv8 model, the BDI-YOLO model in accuracy mAP@50 and mAP@50:95 has increased by 3.8% and 2.7% respectively, with a 4% increase in recall, a 9.4% decrease in computational complexity, and a 28.8% decrease in parameter count. …”
Get full text

Facial morphology prediction after complete denture restoration based on principal component analysis by Cheng Cheng, Xiaosheng Cheng, Ning Dai, Tao Tang, Zhenteng Xu, Jia Cai

“…Firstly, the curvature feature template with few feature points is constructed to replace the deformed areas of facial models. …”
Get full text

An Innovative Inversion Method of Potato Canopy Chlorophyll Content Based on the AFFS Algorithm and the CDE-EHO-GBM Model by Xiaofei Yang, Qiao Li, Honghui Li, Hao Zhou, Jinyan Zhang, Xueliang Fu

Get full text

Generating Human-Interpretable Rules from Convolutional Neural Networks by Russel Pears, Ashwini Kumar Sharma

Get full text

ADMNet: adaptive deformable convolution large model combining multi-level progressive fusion for Building Change Detection by Liye Mei, Haonan Yu, Zhaoyi Ye, Chuan Xu, Cheng Lei, Wei Yang

Get full text