GLS-YOLO: A Lightweight Tea Bud Detection Model in Complex Scenarios by Shanshan Li, Zhe Zhang, Shijun Li

“…To address the demand for high-precision yet lightweight tea bud detection, this study proposes the GLS-YOLO detection model, based on YOLOv8. …”
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Electrochemical detection of procaine hydrochloride anesthetic using diamond-graphene composite electrodes by Guangke Wang, Guodong Leng, Juan Cao

“…This research presents a new electrochemical sensor that can detect procaine hydrochloride and p-aminobenzoic acid (PABA) at the same time. …”
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Harnessing self-supervised learning to boost malicious traffic detection with enhanced attention by SUN Jianwen, ZHANG Bin, LI Hongyu, CHANG Heyu

“…The existing deep learning-based malicious traffic detection methods generally suffered from three main problems: labeled sample scarcity, inadequate representation of malicious behavior traffic features, and a high false positive rate due to ineffective integration of behavioral association patterns during detection. …”
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Feature Generation-Based Fingerprint Liveness Detection: A Novel Multimodal Approach by B. R. Rajakumar, S. Amala Shanthi

“…This averts the usage of memory to store both fingerprint and iris features on the detection side. To further effectuate the detection process, an Adaptive Focal Loss (AFL) is proposed in this paper. …”
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YOLO-LPSS: A Lightweight and Precise Detection Model for Small Sea Ships by Liran Shen, Tianchun Gao, Qingbo Yin

“…We propose YOLO-LPSS, a novel model designed to significantly improve small ship detection accuracy with low computation cost. The characteristics of YOLO-LPSS are as follows: (1) Strengthening the backbone’s ability to extract and emphasize features relevant to small ship objects, particularly in semantic-rich layers. (2) A sophisticated, learnable method for up-sampling processes is employed, taking into account both deep image information and semantic information. (3) Introducing a post-processing mechanism in the final output of the resampling process to restore the missing local region features in the high-resolution feature map and capture the global-dependence features. …”
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Sensor Fusion Method for Object Detection and Distance Estimation in Assisted Driving Applications by Stefano Favelli, Meng Xie, Andrea Tonoli

“…The fusion of multiple sensors’ data in real-time is a crucial process for autonomous and assisted driving, where high-level controllers need classification of objects in the surroundings and estimation of relative positions. …”
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Intelligent Deep Learning and Keypoint Tracking-Based Detection of Lameness in Dairy Cows by Zongwei Jia, Yingjie Zhao, Xuanyu Mu, Dongjie Liu, Zhen Wang, Jiangtan Yao, Xuhui Yang

“…With the ongoing development of computer vision technologies, the automation of lameness detection in dairy cows urgently requires improvement. …”
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Detection of Mycobacterium avium subsp. paratuberculosis by a Direct In Situ PCR Method by Fernando Delgado, Diana Aguilar, Sergio Garbaccio, Gladys Francinelli, R. Hernández-Pando, María Isabel Romano

“…Although the technique was useful for Map detection, the signal was lower than immunohistochemistry probably because of the fixation process. …”
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URDD: An open dataset for urban roadway disease detection and classificationMendeley Data by Shuaiqi Liu, Wenjing Jiang, Yue Yu, Lei Ren, Chunbo Li, Qi Hu

“…This process is time-consuming and subjective. Deep learning, especially convolutional neural networks (CNNs), has proven highly effective in image recognition and object detection. …”
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Integrating Explanations into CNNs by Adopting Spiking Attention Block for Skin Cancer Detection by Inzamam Mashood Nasir, Sara Tehsin, Robertas Damaševičius, Rytis Maskeliūnas

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Implementation Outcomes for Agitation Detection Technologies in People with Dementia: A Systematic Review by Nicolas Farina, Lorna Smith, Melissa Rajalingam, Sube Banerjee

“…Using technologies to detect agitation can help monitor and intervene when agitation occurs, potentially reducing overall care and support needs. …”
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Review on Application of Machine Learning in Detecting Suicidal Ideation for Social Media Users by MENG Xiuyang, WANG Shiyi, LI Dudu, WANG Chunling

“…Firstly, this paper provides an overview of the definition, process, commonly employed methods, and evaluation indicators for detecting suicidal ideation. …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
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Cross-Scale Hypergraph Neural Networks with Inter–Intra Constraints for Mitosis Detection by Jincheng Li, Danyang Dong, Yihui Zhan, Guanren Zhu, Hengshuo Zhang, Xing Xie, Lingling Yang

“…Additionally, we leverage hypergraph convolutional networks to process both intracellular and intercellular information, leading to more precise diagnostic outcomes. …”
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Research on Seamless Fabric Defect Detection Based on Improved YOLOv8n by Qin Sun, Bernd Noche, Zongyi Xie, Bingqiang Huang

“…An improved YOLOv8n seamless fabric defect detection model is proposed to solve the current issues in seamless fabric defects in factories in this paper. …”
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Data Quality Monitoring for the Hadron Calorimeters Using Transfer Learning for Anomaly Detection by Mulugeta Weldezgina Asres, Christian Walter Omlin, Long Wang, David Yu, Pavel Parygin, Jay Dittmann, the CMS-HCAL Collaboration

“…Despite the triumph of TL in fields like computer vision and natural language processing, efforts on complex ST models for anomaly detection (AD) applications are limited. …”
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Detection of Mucous Retention Cysts Using Deep Learning Methods on Panoramic Radiographs by Seda Arslan Tuncer, Çağla Danacı, Sümeyye Coşgun Baybars

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UnidecNMR: automatic peak detection for NMR spectra in 1-4 dimensions by Charles Buchanan, Gogulan Karunanithy, Olga Tkachenko, Michael Barber, Michael T. Marty, Timothy J. Nott, Christina Redfield, Andrew J. Baldwin

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Transfer Learning and Semisupervised Adversarial Detection and Classification of COVID-19 in CT Images by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Son Tung Ngo, Thang Van Doan, Son Ba Nguyen, Son Hoang Nguyen

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A Novel Semantic Driven Meta-Learning Model for Rare Attack Detection by Y. Annie Jerusha, S. P. Syed Ibrahim, Vijay Varadharajan

“…It uses advanced learning techniques to improve detection through a two-stage verification process. …”
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