Automatic pine wilt disease detection based on improved YOLOv8 UAV multispectral imagery by Shaoxiong Xu, Wenjiang Huang, Dacheng Wang, Biyao Zhang, Hong Sun, Jiayu Yan, Jianli Ding, Jinjie Wang, Qiuli Yang, Tiecheng Huang, Xu Ma, Longlong Zhao, Zhuoqun Du

“…A dataset of optimal spectral combinations from visible light and multispectral images was constructed, along with an improved YOLOv8 deep learning model for rapid and accurate identification of PWD-infected trees. …”
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Improving TMJ Diagnosis: A Deep Learning Approach for Detecting Mandibular Condyle Bone Changes by Kader Azlağ Pekince, Adem Pekince, Buse Yaren Kazangirler

“…The aim of this study is to enable the detection and diagnosis of mandibular condyle degenerations, which are difficult to observe and diagnose on panoramic radiographs, using deep learning methods. …”
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The Neural Frontier of Future Medical Imaging: A Review of Deep Learning for Brain Tumor Detection by Tarek Berghout

“…By analyzing over 100 research papers over past half-decade (2019–2024), this review fills that gap, exploring the latest methods and paradigms, summarizing key concepts, challenges, datasets, and offering insights into future directions for brain tumor detection using deep learning. …”
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PA2E: Real-Time Anomaly Detection With Hyperspectral Imaging for Food Safety Inspection by Jungi Lee, Myounghwan Kim, Jiseong Yoon, Kwangsun Yoo, Seok-Joo Byun

“…Hyperspectral imaging captures material-specific spectral data, making it effective for detecting contaminants in food that are challenging to identify using conventional methods. …”
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DC-Mamba: A Novel Network for Enhanced Remote Sensing Change Detection in Difficult Cases by Junyi Zhang, Renwen Chen, Fei Liu, Hao Liu, Boyu Zheng, Chenyu Hu

“…Nevertheless, existing Mamba-based methods lack optimization for complex change areas, making it easy to lose shallow features or local features, which leads to poor performance on challenging detection cases and high-difficulty datasets. …”
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MRC-DETR: A High-Precision Detection Model for Electrical Equipment Protection in Power Operations by Shenwang Li, Yuyang Zhou, Minjie Wang, Li Liu, Thomas Wu

“…Our method introduces two technical innovations: a Multi-Scale Enhanced Boundary Attention (MEBA) module, which significantly improves the detection of small and occluded targets through optimized feature representation, and a knowledge distillation strategy that enables efficient deployment on edge devices. …”
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Construction of advanced persistent threat attack detection model based on provenance graph and attention mechanism by Yuancheng LI, Hao LUO, Xinyu WANG, Jiexuan YUAN

“…In response to the difficulty of existing attack detection methods in dealing with advanced persistent threat (APT) with longer durations, complex and covert attack methods, a model for APT attack detection based on attention mechanisms and provenance graphs was proposed.Firstly, provenance graphs that described system behavior based on system audit logs were constructed.Then, an optimization algorithm was designed to reduce the scale of provenance graphs without sacrificing key semantics.Afterward, a deep neural network (DNN) was utilized to convert the original attack sequence into a semantically enhanced feature vector sequence.Finally, an APT attack detection model named DAGCN was designed.An attention mechanism was applied to the traceback graph sequence.By allocating different weights to different positions in the input sequence and performing weight calculations, sequence feature information of sustained attacks could be extracted over a longer period of time, which effectively identified malicious nodes and reconstructs the attack process.The proposed model outperforms existing models in terms of recognition accuracy and other metrics.Experimental results on public APT attack datasets show that, compared with existing APT attack detection models, the accuracy of the proposed model in APT attack detection reaches 93.18%.…”
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How, What, and Where You Sample Environmental DNA Affects Diversity Estimates and Species Detection by Anish Kirtane, Leif Howard, Caitlin E. Beaver, Margaret E. Hunter, Gordon Luikart, Kristy Deiner

“…In comparison, the beta diversity of plant eDNA was less impacted by the sampling method. We found no clear difference in detection for the invasive species targets based on the eDNA sampling method. …”
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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…On the other hand, the proposed intelligent voyage optimization algorithm-based Radial basis neural network (IntVO-RBNN) effectively detects the attacks in the network. …”
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Deployment cost minimization for composite event detection in large-scale heterogeneous wireless sensor networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

“…Most of the traditional methods are focusing on atomic event detection which only needs one type of homogeneous node. …”
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DMAC: Discovering Multi-Attribute Correlations of Deep Quality Features for Defect Detection in Mechanical Components by Yue Yu

“…Experimental results on datasets from multiple mechanical component assessments demonstrate that DMAC effectively uncovers complex feature interactions, offering adaptive, data-driven optimization for a responsive defect detection system. …”
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A Multi-Strategy Active Learning Framework for Enhanced Peripheral Blood Cell Image Detection by Yuheng Feng, Jiangtao He, Linjin Wang, Wuchen Yang, Sihan Deng, Lanlin Li, Xinwei Li

“…However, existing methods typically focus on a limited number of cell types (usually 3 to 10), restricting their ability to detect a broader range of cells. …”
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Enhancing EEG-Based Emotion Detection with Hybrid Models: Insights from DEAP Dataset Applications by Badr Mouazen, Ayoub Benali, Nouh Taha Chebchoub, El Hassan Abdelwahed, Giovanni De Marco

“…Emotion detection using electroencephalogram (EEG) signals is a rapidly evolving field with significant applications in mental health diagnostics, affective computing, and human–computer interaction. …”
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Adulteration Detection and Origin Identification of Yak Milk Powder Based on Near-infrared Spectroscopy Technology by Haiyang PENG, Zhongdong WU, Tao LIN, Hongcheng LIU, Ying GU

“…Traditional DNA detection methods and isotope analysis showed long detection time, which were inapplicable to rapid, low-cost on-site analysis. …”
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Proactive Detection of Malicious Webpages Using Hybrid Natural Language Processing and Ensemble Learning Techniques by Althaf Ali A, Rama Devi K, Syed Siraj Ahmed N, Ramchandran P, Parvathi S

“…The proliferation of malicious webpages presents a growing threat to online security, necessitating advanced detection methods to mitigate risks. This paper proposes a novel approach that integrates Natural Language Processing (NLP) techniques with an ensemble of machine learning models for the proactive detection of malicious web content. …”
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DFC-Net: Dual-Branch Collaborative Feature Enhancement for Cloud Detection in Remote Sensing Images by Wanting Zhou, Yan Mo, Qiaofeng Ou, Shaowei Bai

“…Although deep learning-based methods have achieved remarkable results, challenges remain in the fine-grained segmentation of cloud boundaries and the detection of thin clouds over complex land surfaces. …”
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Beyond conventional vision: RGB-event fusion for robust object detection in dynamic traffic scenarios by Zhanwen Liu, Yujing Sun, Yang Wang, Nan Yang, Shengbo Eben Li, Xiangmo Zhao

“…Specifically, we design an event correction module (ECM) that temporally aligns asynchronous event streams with their corresponding image frames through optical-flow-based warping. The ECM is jointly optimized with the downstream object detection network to learn task-ware event representations. …”
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Machine Learning-Based Mooring Failure Detection for FPSOs: A Two-Step ANN Approach by Omar Jebari, Do-Soo Kwon, Sung-Jae Kim, Chungkuk Jin, Moohyun Kim

“…Hyperparameter optimization was performed using Bayesian and random search methods, and multiple input variable sets were evaluated. …”
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DAPONet: A Dual Attention and Partially Overparameterized Network for Real-Time Road Damage Detection by Weichao Pan, Jianmei Lei, Xu Wang, Chengze Lv, Gongrui Wang, Chong Li

“…Existing methods for detecting road damage mainly depend on manual inspections or sensor-equipped vehicles, which are inefficient, have limited coverage, and are susceptible to errors and delays. …”
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TdT/Cas12a-based biosensor for sensitive detection of DNA breakpoints in sperm cryopreservation by Bianbian Gao, Ziyang Liu, Bei Yan, Kunhao Du, Liguo Pei, Juan Wang

“…This platform not only represents a significant advancement in DNA damage detection and monitoring but also supports the optimization of cryopreservation protocols and contributes to improving the success and safety of ART. …”
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