A High-Accuracy Underwater Object Detection Algorithm for Synthetic Aperture Sonar Images by Jiahui Su, Deyin Xu, Lu Qiu, Zhiping Xu, Lixiong Lin, Jiachun Zheng

“…Underwater object detection with Synthetic Aperture Sonar (SAS) images faces many problems, including low contrast, blurred edges, high-frequency noise, and missed small objects. …”
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CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Secondly, to overcome the problems of positional information deviation and feature redundancy during multi-scale feature fusion, we design a Feature Recalibration Module (FRM) and a Sandwich Fusion Module. …”
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DAHD-YOLO: A New High Robustness and Real-Time Method for Smoking Detection by Jianfei Zhang, Chengwei Jiang

“…However, the existing smoking behavior detection models based on object detection still have problems, including poor accuracy and insufficient real-time performance. …”
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YOLOv11-HRS: An Improved Model for Strawberry Ripeness Detection by Jianhua Liu, Jing Guo, Suxin Zhang

“…To address these problems, an efficient strawberry ripeness detection model, YOLOv11-HRS, is proposed. …”
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A Disentangled Representation-Based Multimodal Fusion Framework Integrating Pathomics and Radiomics for KRAS Mutation Detection in Colorectal Cancer by Zhilong Lv, Rui Yan, Yuexiao Lin, Lin Gao, Fa Zhang, Ying Wang

“…However, there are still two major problems in existing studies: inadequate single-modal feature learning and lack of multimodal phenotypic feature fusion. …”
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HTTD: A Hierarchical Transformer for Accurate Table Detection in Document Images by Mahmoud SalahEldin Kasem, Mohamed Mahmoud, Bilel Yagoub, Mostafa Farouk Senussi, Mahmoud Abdalla, Hyun-Soo Kang

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Insulator Defect Detection in Complex Environments Based on Improved YOLOv8 by Yuxin Qin, Ying Zeng, Xin Wang

“…To solve the problems of its low accuracy, high delay, and large model size in complex environments, following the principle of progressive extraction from high-entropy details to low-entropy semantics, an improved YOLOv8 target detection network for insulator defects based on bidirectional weighted feature fusion was proposed. …”
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3D Object Detection Based on Graph Network Fusion Sampling Strategy by LI Wenju, CHEN Zhilin, QU Jiantao, CUI Liu, CHU Wanghui, GAO Hui

“…Secondly, the K-NN algorithm is used to construct the graph of the sampled point cloud, and sub-image sampling is introduced to solve the problem of over-smooth graph convolution. Finally, the features of graph nodes are updated through feature interaction to improve the feature extraction ability of the network, thereby improving the target detection effect. …”
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Flooded Infrastructure Change Detection in Deeply Supervised Networks Based on Multi-Attention-Constrained Multi-Scale Feature Fusion by Gang Qin, Shixin Wang, Futao Wang, Suju Li, Zhenqing Wang, Jinfeng Zhu, Ming Liu, Changjun Gu, Qing Zhao

“…On the one hand, land cover data are not updated in time, resulting in the misjudgment of disaster losses; on the other hand, since buildings block floods, the above methods cannot detect flooded buildings. Automated change-detection methods can effectively alleviate the above problems. …”
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DScanNet: Packaging Defect Detection Algorithm Based on Selective State Space Models by Yirong Luo, Yanping Du, Zhaohua Wang, Jingtian Mo, Wenxuan Yu, Shuihai Dou

“…To address the problem that the model’s detailed feature extraction for small target defects is not sufficient and thus leads to low detection accuracy, the MEFE module, the local feature extraction module (LFEM Block), and the PCR module of the multi-scale convolution and feature enhancement strategy are proposed to enhance the model’s capability of capturing defective features and focusing on specific features, and to improve the detection accuracy. …”
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Pixel-Based Change Detection in Moving-Camera Videos Using Twin Convolutional Features on a Data-Constrained Scenario by Luiz G. C. Tavares, Allan F. Da Silva, Rafael Padilla, Lucas A. Thomaz, Sergio L. Netto, Eduardo A. B. Da Silva

“…To address these moving camera surveillance problems, the PBCD-MC method was developed based on a hybrid ensemble feature extractor, combining deep learning methods, responsible for generating high-level features, and tree-based algorithms, responsible for selecting and combining the deep features. …”
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Enhanced UAV Detection and Classification With Birds Using NLFM Pulse-Doppler Radar by Ju-Hong Park, Yoo-Ho Jang, Sang-Hoon Kang, He-Won Jung, Seong-Ook Park

“…Detecting UAVs in clutter environments and classification with birds is a difficult and important problem. …”
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A Novel Detection-and-Replacement-Based Order-Operator for Differential Evolution in Solving Complex Bound Constrained Optimization Problems by Sichen Tao, Sicheng Liu, Shoya Ohta, Ruihan Zhao, Zheng Tang, Yifei Yang

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A multi-scale small object detection algorithm SMA-YOLO for UAV remote sensing images by Shilong Zhou, Haijin Zhou, Lei Qian

“…Abstract Detecting small objects in complex remote sensing environments presents significant challenges, including insufficient extraction of local spatial information, rigid feature fusion, and limited global feature representation. …”
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Acoustic-based machine learning approaches for depression detection in Chinese university students by Yange Wei, Yange Wei, Shisen Qin, Fengyi Liu, Rongxun Liu, Yunze Zhou, Yuanle Chen, Xingliang Xiong, Wei Zheng, Guangjun Ji, Yong Meng, Fei Wang, Fei Wang, Ruiling Zhang

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Technologies and Algorithms for Building the Augmented Reality by I. A. Blagoveshchenskiy, N. A. Demyankov

“…The authors give a short description and the main characteristics only of two of them: genetic algorithms and feature detection & description. For a programmatic implementation of those algorithms one can use special libraries like OpenCV and AForge.NET, also mentioned in the article. …”
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X-SPIDE: An eXplainable Machine Learning Pipeline for Detecting Smart Ponzi Contracts in Ethereum by Luca Pennella, Fabio Pinelli, Letterio Galletta

“…Consequently, there is a growing need to develop automatic detection mechanisms for such scams. So far, the problem has been tackled by considering only classifier performances and with limited focus on the explanation and interpretation of the results. …”
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Development and performance evaluation of a Bengali-adapted mHealth app for early detection of impaired visual acuity by Monzurul Haque, Marzia Zaman, Ashraful Islam, Farhana Sarker, Nahid Ferdausi, Khondaker A. Mamun

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MFFNet: a building change detection method based on fusion of spectral and geometric information by Zhihao Guo, Jianping Pan, Peng Xie, Ling Zhu, Chen Qi, Xunxun Wang, Yihan Yang, Yan Wang, Huijuan Zhang, Zhaohui Ren

“…However, when using remote sensing images, shadows, vegetation and objects with similar spectral and morphological characteristics as buildings can cause false detections, omissions and incomplete patch edges. To address this issue, we develop the multiscale feature fusion network for dual-modal data (MFFNet), which has two main aspects: (1) The multi-dual-modal feature fusion module detects changes in features with similar spectral and morphological characteristics as buildings. …”
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FD-IDS: Federated Learning with Knowledge Distillation for Intrusion Detection in Non-IID IoT Environments by Haonan Peng, Chunming Wu, Yanfeng Xiao

“…Together, these mechanisms effectively alleviate the problem of model drift. Experiments conducted on both the Edge-IIoT and N-BaIoT datasets demonstrate that FD-IDS achieves promising detection performance across multiple evaluation metrics.…”
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