Deep Embedded Auto-encoder for End-to-End Unsupervised Image Anomaly Detection by Xuan Huang, Hailin Tang

“…Abstract Image anomaly detection plays a critical role in industrial quality control, medical diagnostics, and security surveillance, yet existing unsupervised methods often suffer from limited detection accuracy and poor adaptability. …”
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IRFNet: Cognitive-Inspired Iterative Refinement Fusion Network for Camouflaged Object Detection by Guohan Li, Jingxin Wang, Jianming Wei, Zhengyi Xu

“…Camouflaged Object Detection (COD) aims to identify objects that are intentionally concealed within their surroundings through appearance, texture, or pattern adaptations. …”
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Battery System Fault Detection: A Data-Driven Aggregation and Augmentation Strategy by Zhiming Zhang, Dan Zhang, Dejun Li, Yi Liu, Jiong Yang

“…In applying machine learning to battery system fault detection, current methods encounter some challenges. …”
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Detection of DDoS Attacks in SDN Switches with Deep Learning and Swarm Intelligence Approach by Mohsen Eghbali, Mohammadreza Mollkhalili Maybodi

“…The proposed method outperforms feature selection methods based on WOA, HHO, and AO algorithms, and deep learning methods like LSTM, RNN, and CNN, particularly in detecting DDoS attacks.…”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…However, existing detection methods face challenges such as small target detection, severe occlusion, and changing traffic conditions. …”
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Enhancing Disease Detection in the Aquaculture Sector Using Convolutional Neural Networks Analysis by Hayin Tamut, Robin Ghosh, Kamal Gosh, Md Abdus Salam Siddique

“…The expansion of aquaculture necessitates innovative disease detection methods to ensure sustainable production. …”
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Infectious Hypodermal and Hematopoietic Necrosis Virus Detection in Shrimp Farming Pond Sediments by Ruoxuan LÜ, Xiuhua WANG, Meifeng WANG, Xinyu LIAN, Chen LI, Hua XU, Weili YIN, Peng JIA, Bing YANG

“…For instance, for a method has been developed for detecting Cyprinid herpesvirus 3 (CyHV-3) in environmental waters using virus concentration methods and TaqMan polymerase chain reaction (PCR). …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…The method automatically identifies clusters of varying densities while filtering out noise, ensuring a more precise change detection process. …”
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SGSNet: a lightweight deep learning model for strawberry growth stage detection by Zhiyu Li, Jianping Wang, Guohong Gao, Yufeng Lei, Chenping Zhao, Yan Wang, Haofan Bai, Yuqing Liu, Xiaojuan Guo, Qian Li

“…IntroductionDetecting strawberry growth stages is crucial for optimizing production management. …”
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DAM-Net: Domain Adaptation Network With Microlabeled Fine-Tuning for Change Detection by Hongjia Chen, Xin Xu, Fangling Pu

“…Change detection (CD) in remote sensing imagery plays a crucial role in various applications, such as urban planning, damage assessment, and resource management. …”
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Data augmentation based multi-view contrastive learning graph anomaly detection by LI Yifan, LI Jiayin, LIN Xingpeng, DAI Yuanfei, XU Li

“…Although contrast-based anomaly detection methods could effectively mine anomaly information based on the inconsistency of anomalous node instance pairs, avoiding the drawback of using self-coding architecture that led to the need for full graph training for the model. …”
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A comprehensive review on optical and electrochemical aptasensor for detection of fumonisin B1 by Jiayu Ma, Xiaodong Guo, Xiaodong Guo

“…Leveraging their high specificity and strong affinity for target molecules, aptamers have been successfully employed as alternatives to conventional methods for FB1 detection, leading to the development of diverse aptasensor platforms. …”
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ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest by Andrey Ageev, Andrei Konstantinov, Lev Utkin

“…Through extensive experimentation across diverse datasets, ADA-NAF demonstrates superior performance compared to state-of-the-art methods. The model shows particular strength in handling high-dimensional data and capturing subtle anomalies that traditional methods often do not detect. …”
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Enhancing Environmental DNA Sampling Efficiency for Cetacean Detection on Whale Watching Tours by Lauren Kelly Rodriguez, Belén García Ovide, Eleonora Barbaccia, Jana Robertson, Taïme Smit Pellure, Ángela Ceballos‐Caro, Caterina Lanfredi, Maddalena Jahoda, Enrico Villa, Arianna Azzellino, Marianne Helene Rasmussen, Michael Traugott, Bettina Thalinger

“…However, eDNA research is still evolving, with ongoing efforts to optimize field sampling and laboratory protocols. Building on the challenges of conventional monitoring methods, this study sought to refine eDNA sampling parameters to offer a more efficient and scalable approach for cetacean research, leveraging citizen science platforms. …”
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Utilizing Detectron2 for accurate and efficient colon cancer detection in histopathological images by Luxi Chen, Jie Shen, Xinyu Li, Rongzhou Li, Xiaoyun Gao, Xiaoyun Gao, Xinyue Chen, Xinyue Chen, Xiaotian Pan, Xiaotian Pan, Xiaosheng Jin

“…Recent advances in deep learning have shown promise in medical image analysis, offering potential improvements in detection accuracy and efficiency.MethodsThis study proposes a novel approach for classifying colon tissue images as normal or cancerous using Detectron2, a deep learning framework known for its superior object detection and segmentation capabilities. …”
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Development and Application of Indirect ELISA for IBDV VP2 Antibodies Detection in Poultry by Wenying Zhang, Yulong Wang, Guodong Wang, Hangbo Yu, Mengmeng Huang, Yulong Zhang, Runhang Liu, Suyan Wang, Hongyu Cui, Yanping Zhang, Yuntong Chen, Yulong Gao, Xiaole Qi

“…This approach enabled the establishment of an indirect ELISA method for detecting IBDV VP2 antibody (VP2-ELISA). …”
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Evaluation of Feature Transformation and Machine Learning Models on Early Detection of Diabetes Mellitus by Ahmed Ali Linkon, Inshad Rahman Noman, Md Rashedul Islam, Joy Chakra Bortty, Kanchon Kumar Bishnu, Araf Islam, Rakibul Hasan, Masuk Abdullah

“…The increasing prevalence of diabetes necessitates the development of effective early detection methods to mitigate its health impacts. This paper investigates the impact of feature transformation and machine learning (ML) models on the early detection of diabetes using a binary tabular classification dataset. …”
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Near Miss Detection Using Distancing Monitoring and Distance-Based Proximal Indicators by Lek Ming Lim, Lu Yang, Wen Zhu, Ahmad Sufril Azlan Mohamed, Majid Khan Majahar Ali

“…The experiment employed methods for vehicle detection through the monitoring system. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…Traditional methods for detecting plant diseases and pests are time-consuming, labor-intensive, and require specialized skills and resources, making them insufficient to meet the demands of modern agricultural development. …”
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PREDICTIVE MODELS FOR EARLY DETECTION OF PARKINSON’S DISEASE: A MACHINE LEARNING APPROACH by S. Jeyantha Jafna Juliet, D. Jasmine David, J. S. Raj Kumar, Angelin Jeba P., R. Golden Nancy, M. Selvarathi, T. Jemima Jebaseeli

“…By applying the hyperparameter optimization process, the accuracy is estimated. When used to diagnose Parkinson's disease (PD), the proposed methods produce accuracy rates of 98.9% for Naive Bayes and 97.3% for Logistic Regression.…”
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