MapSAM: adapting segment anything model for automated feature detection in historical maps by Xue Xia, Daiwei Zhang, Wenxuan Song, Wei Huang, Lorenz Hurni

“…The proposed MapSAM framework demonstrates promising performance across three distinct historical map segmentation tasks: railway, vineyard, and building block detection. Experimental results show that it adapts well to various features, even when fine-tuned with extremely limited data (e.g. 10 shots). …”
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Improved YOLOv8s-based foreign object detection method for mine conveyor belts by LI Runze, GUO Xingge, YANG Fazhan, ZHAO Peipei, XIE Guolong

“…A parameter-sharing lightweight detection head was designed, using Group Normalization (GN) as the basic convolutional normalization block to compensate for accuracy loss caused by model lightweighting. …”
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A Hierarchical Local-Sparse Model for Semantic Change Detection in Remote Sensing Imagery by Fachuan He, Hao Chen, Shuting Yang, Zhixiang Guo

“…In response to the existing challenges in semantic change detection (SCD) for remote sensing images, such as weak spatiotemporal correlation and insufficient utilization of local neighborhood information, this article proposes a SCD network based on hierarchical local-sparse attention (HLSNet). …”
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Efficient detection of highway pavement cracks using computer vision-based MSFNet model by Zhengfa Jiang, Danlan Li, Ting Zhao, Mingxing Gao

“…At the same time, the inference speed reaches 47.8FPS, which meets the actual application needs of pavement crack detection.…”
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UCN-YOLOv5: Traffic Sign Object Detection Algorithm Based on Deep Learning by Peilin Liu, Zhaoyang Xie, Taijun Li

“…Traffic sign detection plays an important role in traffic safety and traffic management. …”
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YOLO-PWSL-Enhanced Robotic Fish: An Integrated Object Detection System for Underwater Monitoring by Lingrui Lei, Ying Tang, Weidong Zhang, Quan Tang, Haichi Hao

“…In fact, we designed a multilevel attention fusion block (LGFB) that enhances perception in complex scenarios, to optimize the accuracy of the detected frames, the Wise-ShapeIoU loss function was used, and in order to reduce the parameters and FLOPs of the model, a lightweight convolution method called PConv was introduced. …”
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LI-YOLO: An Object Detection Algorithm for UAV Aerial Images in Low-Illumination Scenes by Songwen Liu, Hao He, Zhichao Zhang, Yatong Zhou

“…With the development of unmanned aerial vehicle (UAV) technology, deep learning is becoming more and more widely used in object detection in UAV aerial images; however, detecting and identifying small objects in low-illumination scenes is still a major challenge. …”
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Early stroke behavior detection based on improved video masked autoencoders for potential patients by Meng Wang, Guanci Yang, Kexin Luo, Yang Li, Ling He

“…To enhance the early perceive and detection of potential stroke patients, the early stroke behavior detection based on improved Video Masked Autoencoders (VideoMAE) for potential patients (EPBR-PS) is proposed. …”
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Deep Learning Evaluation of Glaucoma Detection Using Fundus Photographs in Highly Myopic Populations by Yen-Ying Chiang, Ching-Long Chen, Yi-Hao Chen

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Enhanced YOLOv5s Model for Improved Multi-Sized Object Detection in Road Scenes by Sangavi Sivanandham, Dharanibai Gunaseelan

“…Furthermore, an efficient channel attention (ECA) mechanism is integrated into the backbone to prioritize key feature channels, thereby enhancing the model’s ability to detect overlapping and small objects. To improve the feature fusion process, a Multi-scale BiFPN block is integrated into the neck of the model. …”
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A detection algorithm for small surface floating objects based on improved YOLOv5s by Xusheng YUE, Jun LI, Yaohong WANG, Penghao ZHU, Zhexing WANG, Xuanhao XU

“…Third, the CBAM (Convolutional Block Attention Module) was incorporated into the backbone network to address the limited feature extraction capability for detecting floating bottles on the water surface. …”
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MINDS: Detection of an Inner Gas Disk Caused by Evaporating Bodies around HD 172555 by Matthias Samland, Thomas Henning, Alessio Caratti o Garatti, Teresa Giannini, Jeroen Bouwman, Benoît Tabone, Aditya M. Arabhavi, Göran Olofsson, Manuel Güdel, Nicole Pawellek, Inga Kamp, L. B. F. M. Waters, Dmitry Semenov, Ewine F. van Dishoeck, Olivier Absil, David Barrado, Anthony Boccaletti, Valentin Christiaens, Danny Gasman, Sierra L. Grant, Hyerin Jang, Till Kaeufer, Jayatee Kanwar, Giulia Perotti, Kamber Schwarz, Milou Temmink

“…Debris disks trace the leftover building blocks of planets, and thus also planetary composition. …”
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Oriented SAR Ship Detection Based on Edge Deformable Convolution and Point Set Representation by Tianyue Guan, Sheng Chang, Yunkai Deng, Fengli Xue, Chunle Wang, Xiaoxue Jia

“…This methodology enables the precise detection of multi-directional ship targets even in dense scenes. …”
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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…To address these challenges, we propose FQDNet, a novel RGB-IR object detection network that integrates an optimized fusion strategy with a Quad-Head detection framework. …”
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A Lightweight Network for UAV Multi-Scale Feature Fusion-Based Object Detection by Sheng Deng, Yaping Wan

“…The neck network integrates a Multi-Scale Fusion Block (MSFB) to combine multi-level features, further boosting detection precision. …”
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Detection of underground personnel safety helmet wearing based on improved YOLOv8n by WANG Qi, XIA Lufei, CHEN Tianming, HAN Hongyin, WANG Liang

“…Existing methods for detecting safety helmet wearing among underground personnel fail to consider factors such as occlusion, small target size, and background interference, leading to poor detection accuracy and insufficient model lightweighting. …”
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SCL-YOLOv11: A Lightweight Object Detection Network for Low-Illumination Environments by Shulong Zhuo, Hao Bai, Lifeng Jiang, Xiaojian Zhou, Xu Duan, Yiqun Ma, Zihan Zhou

“…In response to the challenges of reduced detection accuracy and high edge-deployment costs encountered by mainstream single-stage object detection models under low-light conditions, this paper proposes a lightweight object detection network based on YOLOv11, integrates StarNet, C3k2-Star, and a lightweight detail-enhanced convolution and shared convolutional detection head(LSDECD), so called SCL-YOLOv11 herein. …”
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A Hybrid Deep Learning Framework for Deepfake Detection Using Temporal and Spatial Features by Fazeel Zafar, Talha Ahmed Khan, Salas Akbar, Muhammad Talha Ubaid, Sameena Javaid, Kushsairy Abdul Kadir

“…This method ensures face detection and alignment by focusing on facial regions. …”
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Detection of Surface Defects in Steel Based on Dual-Backbone Network: MBDNet-Attention-YOLO by Xinyu Wang, Shuhui Ma, Shiting Wu, Zhaoye Li, Jinrong Cao, Peiquan Xu

“…To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. …”
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NST-YOLO11: ViT Merged Model with Neuron Attention for Arbitrary-Oriented Ship Detection in SAR Images by Yiyang Huang, Di Wang, Boxuan Wu, Daoxiang An

“…Due to the significant discrepancies in the distribution of ships in nearshore and offshore areas, the wide range of their size, and the randomness of target orientation in the sea, traditional detection models in the field of computer vision struggle to achieve performance in SAR image ship target detection comparable to that in optical image detection. …”
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