IEAM: Integrating Edge Enhancement and Attention Mechanism with Multi-Path Complementary Features for Salient Object Detection in Remote Sensing Images by Fubin Zhang, Zichi Zhang

“…To address these challenges, we integrate edge enhancement and attention mechanisms with multi-path complementary features for salient object detection in remote sensing images (IEAM), aiming to improve salient target accuracy, boundary detection, and memory efficiency. …”
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Research on damage detection technology for wind turbine blade acoustic signals by fusion of sparse representation, compressive sensing and deep learning by Liang Wang, Chun Yang, Chao Yuan, Yanan Liu, Yanqing Chen

“…The sparse representation method is used to effectively encode the voiceprint signal and extract representative signal features; the compressed sensing technology is applied to efficiently reconstruct the signal using a small amount of sampled data, significantly reducing the data collection amount and storage requirements; deep feature learning and damage pattern classification based on convolutional neural network further improve the accuracy and intelligence level of detection.The research results show that the proposed method effectively reduces the computational complexity and greatly improves the detection accuracy. …”
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Enhancing Autonomous Truck Navigation in Underground Mines: A Review of 3D Object Detection Systems, Challenges, and Future Trends by Ellen Essien, Samuel Frimpong

“…Integrating autonomous haulage systems into underground mining has revolutionized safety and operational efficiency. However, deploying 3D detection systems for autonomous truck navigation in such an environment faces persistent challenges due to dust, occlusion, complex terrains, and low visibility. …”
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Hybrid Naïve Bayes Models for Scam Detection: Comparative Insights From Email and Financial Fraud by Lebede Ngartera, Mahamat Ali Issaka, Saralees Nadarajah

“…Online scams continue to escalate in scale and sophistication, ranging from deceptive phishing emails to complex financial fraud schemes. These evolving threats have surpassed the capabilities of traditional detection systems, creating an urgent demand for scalable, real-time, and interpretable machine learning solutions. …”
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Hate Speech Detection and Online Public Opinion Regulation Using Support Vector Machine Algorithm: Application and Impact on Social Media by Siyuan Li, Zhi Li

“…Detecting hate speech in social media is challenging due to its rarity, high-dimensional complexity, and implicit expression via sarcasm or spelling variations, rendering linear models ineffective. …”
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Establishment and application of a rapid new detection method for antimicrobial susceptibility testing of Klebsiella pneumoniae based on MALDI-TOF MS by Yapei Zhang, Fanghua Fan, Xuan Wang, Jie Zhu, Shilei Dong

“…Current rapid AST techniques are hampered by factors such as high costs, technological complexities, and limited detection capabilities. We present a novel rapid method and applied to the determination of the susceptibility of K. pneumoniae to imipenem. …”
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Research on multi-view collaborative detection system for UAV swarms based on Pix2Pix framework and BAM attention mechanism by Yan Ding, Qingxin Cao, Bozhi Zhang, Peilin Li, Zhongjiao Shi

“…The system is designed to enhance multi-view image generation and detection algorithms, thereby improving the accuracy and efficiency of object detection across varying perspectives. …”
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Enhancing the Performance of YOLOv9t Through a Knowledge Distillation Approach for Real-Time Detection of Bloomed Damask Roses in the Field by Farhad Fatehi, Hossein Bagherpour, Jafar Amiri Parian

“…Recent developments in deep learning algorithms, especially in convolutional models, have shown significant promise for object detection, highlighting strong possibilities for improving the efficiency of this process. …”
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Accurate Sugarcane Detection and Row Fitting Using SugarRow-YOLO and Clustering-Based Spline Methods for Autonomous Agricultural Operations by Guiqing Deng, Fangyue Zhou, Huan Dong, Zhihao Xu, Yanzhou Li

“…However, sugarcane leaves and stalks intertwine and overlap at this stage. They can form a complex occlusion structure, which poses a greater challenge to target detection. …”
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Computationally Enhanced UAV-Based Real-Time Pothole Detection Using YOLOv7-C3ECA-DSA Algorithm by Siti Fairuz Mat Radzi, Mohd Amiruddin Abd Rahman, Muhammad Khairul Adib Muhammad Yusof, Nurin Syazwina Mohd Haniff, Romi Fadillah Rahmat

“…Although YOLO-based algorithms have been widely adopted for their speed and efficiency in object detection, achieving a balance between high accuracy and low inference time remains a challenge, particularly in scenarios involving small objects and complex features. …”
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Enhanced TumorNet: Leveraging YOLOv8s and U-net for superior brain tumor detection and segmentation utilizing MRI scans by Wisal Zafar, Ghassan Husnain, Abid Iqbal, Ali Saeed Alzahrani, Muhammad Abeer Irfan, Yazeed Yasin Ghadi, Mohammed S. AL-Zahrani, Ramasamy Srinivasaga Naidu

“…The integration of YOLOv8s and U-Net in Enhanced TumorNet offers a powerful solution for the automated analysis of brain tumors in MRI scans, significantly improving detection and segmentation accuracy. This hybrid approach holds great potential for clinical applications, enhancing the efficiency and effectiveness of brain tumor diagnosis.…”
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SMS Scam Detection Application Based on Optical Character Recognition for Image Data Using Unsupervised and Deep Semi-Supervised Learning by Anjali Shinde, Essa Q. Shahra, Shadi Basurra, Faisal Saeed, Abdulrahman A. AlSewari, Waheb A. Jabbar

“…The rationale behind highlighting these models is their potential to significantly improve smishing detection rates. For instance, the high accuracy of the KNN-Flatten model suggests its applicability in real-time spam detection systems, but its computational complexity might limit scalability in large-scale deployments. …”
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Rapid in vitro assessment of the immunogenicity potential of engineered antibody therapeutics through detection of CD4+ T cell interleukin-2 secretion by Yoshiyuki Arata, Shigeki Motoyama, Mariko Yano, Tatsuya Ikuno, Shunsuke Ito, Tomochika Matsushita, Akira Takeiri, Yukari Nishito, Nami Yabuki, Hideaki Mizuno, Zenjiro Sampei, Masayuki Mishima, Masaki Honda, Jumpei Kiyokawa, Hiromi Suzuki, Shuichi Chiba, Mitsuyasu Tabo, Chiyomi Kubo

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RDW-YOLO: A Deep Learning Framework for Scalable Agricultural Pest Monitoring and Control by Jiaxin Song, Ke Cheng, Fei Chen, Xuecheng Hua

“…Due to target diversity, life-cycle variations, and complex backgrounds, traditional pest detection methods often struggle with accuracy and efficiency. …”
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Advancing depth perception in spatial computing with binocular metalenses by Junkyeong Park, Gyeongtae Kim, Junsuk Rho

“…Liu et al. presents a compact binocular metalens-based depth perception system that integrates efficient edge detection through an advanced neural network. …”
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Research on an Apple Recognition and Yield Estimation Model Based on the Fusion of Improved YOLOv11 and DeepSORT by Zhanglei Yan, Yuwei Wu, Wenbo Zhao, Shao Zhang, Xu Li

“…This study introduces APYOLO, an enhanced apple detection algorithm based on an improved YOLOv11, integrated with the DeepSORT tracking algorithm to improve both detection accuracy and operational speed. …”
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A Novel Error Detection due to Joint CRC Aided Denoise-and-Forward Network Coding for Two-Way Relay Channels by Yulun Cheng, Longxiang Yang

“…In wireless two-way (TW) relay channels, denoise-and-forward (DNF) network coding (NC) is a promising technique to achieve spectral efficiency. However, unsuccessful detection at relay severely deteriorates the diversity gain, as well as end-to-end pairwise error probability (PEP). …”
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A novel cluster of improved frilled lizard optimization and multi-ladder gated networks for the detection of cyber-attacks in computer networks by Vandana Dharmapuri, Sushama Rani Dutta

“…The proposed ML-GNUs are used for differentiating diverse attack patterns, and the improved frilled lizard technique is employed to tune the model’s hyper-parameters, reducing computational overhead and enhancing detection performance. The efficiency of the proposed model is assessed utilising both simulated real-time data traffic patterns and the CIC-IDS-2017 benchmark dataset, and standard performance metrics like accuracy, precision, recall, specificity, Matthews correlation coefficient (MCC), and F1-score are analyzed and measured. …”
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YOLO-WTB: Improved YOLOv12n Model for Detecting Small Damage of Wind Turbine Blades From Aerial Imagery by Phat T. Nguyen, Duy C. Huynh, Loc D. Ho, Matthew W. Dunnigan

“…In addition, in the backbone part, we also propose to remove a Convolution module and an Area Attention Concatenate-Convolution-Fusion module and add an improved SoftPool Feature Spatial Pyramid Pooling - Fast module to increase the feature extraction ability while maintaining the complexity of the model. The proposed model not only optimizes wind turbine maintenance efficiency but also contributes to advancements in the field of computer vision.…”
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Enhanced detection of surface deformations in LPBF using deep convolutional neural networks and transfer learning from a porosity model by Muhammad Ayub Ansari, Andrew Crampton, Samer Mohammed Jaber Mubarak

“…Our approach demonstrates the power of transfer learning in adapting a model known for porosity detection in LPBF to identify surface deformations with high accuracy (94%), matching the performance of the best existing models but with significantly less complexity. …”
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