AI Driven Fraud Detection Models in Financial Networks: A Comprehensive Systematic Review by Nusrat Jahan Sarna, Farzana Ahmed Rithen, Umme Salma Jui, Sayma Belal, Al Amin, Tasnim Kabir Oishee, A. K. M. Muzahidul Islam

“…Future research should focus on improving the transparency of the AI model, integrating AI with blockchain for secure data sharing, and leveraging federated learning to enhance fraud detection capabilities. By addressing these challenges, AI can play a pivotal role in securing financial systems, minimizing fraud risks, and fostering cross-industry collaboration for more resilient fraud detection frameworks.…”
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TJ0113-induced mitophagy in acute liver failure detected by Raman microspectroscopy by Chunlian Huang, Jiaqi Liao, Xufeng Cen, Changwei Jiao, Sijia Chen, Dong Liu, Hang-Shuai Qu, Jiansheng Zhu, Sailing He

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Glutathione and Magnetic Nanoparticle-Modified Nanochannels for the Detection of Cadmium (II) in Cereal Grains by Wei Hu, Xinyue Xiang, Donglei Jiang, Na Zhang, Lifeng Wang

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Lung cancer associated autoantibody responses are detectable years before clinical presentation. by Jared Allen, Graham Healey, Isabel Macdonald

“…Using a longitudinal cohort from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) study, we have established that elevated autoantibodies can be detected an average of four years in advance of clinical presentation, and in some cases up to 8 years prior to clinical presentation. …”
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A Weakly Supervised Network for Coarse-to-Fine Change Detection in Hyperspectral Images by Yadong Zhao, Zhao Chen

“…To address these challenges, this paper introduces WSCDNet, a weakly supervised HSI-CD network employing coarse-to-fine feature learning, with key innovations including: (1) A dual-branch detection framework integrating binary and multiclass change detection at the sub-pixel level that enhances collaborative optimization through a cross-feature coupling module; (2) introduction of multi-granularity aggregation and difference feature enhancement module for detecting easily confused regions, which effectively improves the model’s detection accuracy; and (3) proposal of a weakly supervised learning strategy, reducing model sensitivity to noisy pseudo-labels through decision-level consistency measurement and sample filtering mechanisms. …”
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dTOURS: Dense-region tagging for outbreak detection using ratio statistics. by Lukas Wagner, Richa Agarwala

“…Surveillance for food safety in the United States of America is a collaborative effort among public health agencies with additional partners worldwide contributing sequence data. …”
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Exploration of Large language model assisted boulder detection from Lidar data by L. Zhu, E. Hattula, J. Raninen

“…Due to the complexity of working and availability with very high-resolution data for boulder detection, few studies have explored this area. As a result, this research highlights the potential of LLMs in innovative applications and underscores their role in advancing collaborative research efforts to enhance scientific capabilities.…”
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Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…Additionally, a synchronous collaborative motion compensator is developed to improve coordination accuracy between the dual motors. …”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

“…This model effectively improves the efficiency and accuracy of time action detection through the collaborative action of multiple modules, demonstrating good applicability and robustness.…”
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An Improved Low-Cost Continuous Compaction Detection Method for the Construction of Asphalt Pavement by Tong Jia, Tiejun He, Zhendong Qian, Jian Lv, Kaixin Cao

“…For the trajectory of rollers, a collaborative positioning method was proposed. For the monitoring of rolling process, an embedded-based detection system was designed. …”
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Indian SUMO traffic scenario-based misbehaviour detection dataset for connected vehicles by Umesh Bodkhe, Sudeep Tanwar

“…However, these BSMs are susceptible to various security attacks, which disrupt the collaborative functionality of ITS, potentially resulting in accidents or traffic congestion. …”
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A Novel Blockchain-Enabled Federated Learning Scheme for IoT Anomaly Detection by Van-Doan Nguyen, Abebe Diro, Naveen Chilamkurti, Will Heyne, Khoa Tran Phan

“…In this research, we proposed a novel anomaly detection system (ADS) that integrates federated learning (FL) with blockchain for resource-constrained IoT. …”
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FedSW-TSAD: SWGAN-Based Federated Time Series Anomaly Detection by Xiuxian Zhang, Hongwei Zhao, Weishan Zhang, Shaohua Cao, Haoyun Sun, Baoyu Zhang

“…In response to this trend, federated time series anomaly detection enables collaborative analysis across distributed sensing nodes without exposing raw data. …”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…In this paper, we proposed a collaborative approach to detect crime patterns and criminal emotions with the aim of enhancing judiciary decision-making. …”
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Complementary Local–Global Optimization for Few-Shot Object Detection in Remote Sensing by Yutong Zhang, Xin Lyu, Xin Li, Siqi Zhou, Yiwei Fang, Chenlong Ding, Shengkai Gao, Jiale Chen

“…Few-shot object detection (FSOD) in remote sensing remains challenging due to the scarcity of annotated samples and the complex background environments in aerial images. …”
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Federated knowledge distillation for enhanced insulator defect detection in resource‐constrained environments by Xiaohu Huang, Minghui Jia, Xianghua Tai, Wei Wang, Qi Hu, Dongping Liu, Peiheng Guo, Shengxiang Tian, Dequan Yan, Haishan Han

“…Moreover, the asynchronous aggregation approach and model freshness mechanism designed in the method further enhance the training efficiency and collaborative effect. The experimental results show that the detection accuracy and efficiency of this paper's method on public datasets are significantly better than the benchmark algorithm.…”
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Multi-View Intrusion Detection Framework Using Deep Learning and Knowledge Graphs by Min Li, Yuansong Qiao, Brian Lee

“…Experimental results show that the deep fusion strategy of multi-dimensional data overcomes the limitations of traditional single-view models, enables collaborative multi-dimensional analysis of network attack behaviors, and significantly enhances detection capabilities in complex attack scenarios. …”
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Detection Method of Apple Alternaria Leaf Spot Based on Deep-Semi-NMF by FU Zhuojun, HU Zheng, DENG Yangjun, LONG Chenfeng, ZHU Xinghui

“…A comparative analysis was conducted with several other detection methods, including GRX (Reed-Xiaoli detector), LRX (Local Reed-Xiaoli detector), CRD (Collaborative-Representation-Based Detector), LSMAD (LRaSMD-Based Mahalanobis Distance Detector), and the deep learning model Unet. …”
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Service-Chain-Driven Communication and Computing Integration Networking: A Case Study of Levee Piping Hazard Inspection via Remote Sensing by Jing Chen, Lyuzhou Gao, Hongquan Sun, Siquan Yang, Zhonggen Wang, Yuting Wan, Kedi Wang

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FedRecSys: A Federated Learning-Based Recommender System for Concept Drift Adaptation by Anagha Chaudhari, A. A. Hitham Seddig, Roshani Raut, Aliza Sarlan

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