Detection of Apple Leaf Gray Spot Disease Based on Improved YOLOv8 Network by Siyi Zhou, Wenjie Yin, Yinghao He, Xu Kan, Xin Li

“…The details are as follows: (1) we introduce Dynamic Residual Blocks (DRBs) to boost the model’s ability to extract lesion features, thereby improving detection accuracy; (2) add a Self-Balancing Attention Mechanism (SBAY) to optimize the feature fusion and improve the ability to deal with complex backgrounds; and (3) incorporate an ultra-small detection head and simplify the computational model to reduce the complexity of the YOLOv8 network while maintaining the high precision of detection. …”
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An explainable unsupervised learning approach for anomaly detection on corneal in vivo confocal microscopy images by Ningning Tang, Qi Chen, Yunyu Meng, Daizai Lei, Li Jiang, Yikun Qin, Xiaojia Huang, Fen Tang, Shanshan Huang, Qianqian Lan, Qi Chen, Lijie Huang, Rushi Lan, Xipeng Pan, Huadeng Wang, Fan Xu, Wenjing He

“…BackgroundIn vivo confocal microscopy (IVCM) is a crucial imaging modality for assessing corneal diseases, yet distinguishing pathological features from normal variations remains challenging due to the complex multi-layered corneal structure. Existing anomaly detection methods often struggle to generalize across diverse disease manifestations. …”
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Enhancing image quality in circular-view photoacoustic tomography using randomized detection points by Soheil Hakakzadeh, Praveenbalaji Rajendran, Zahra Kavehvash, Manojit Pramanik

“…Circular-view (circular scan) photoacoustic computed tomography (PACT) with low-density detection points (DPs) is an efficient, high-speed, and inexpensive modality with numerous (pre-) clinical applications. …”
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Real-time aerial fire detection on resource-constrained devices using knowledge distillation by Sabina Jangirova, Branislava Jankovic, Waseem Ullah, Latif U. Khan, Mohsen Guizani

“…While these architectures provide high accuracy in fire detection, their computational complexity limits real-time performance on edge devices such as UAVs. …”
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Novel transfer learning based acoustic feature engineering for scene fake audio detection by Ahmad Sami Al-Shamayleh, Hafsa Riasat, Ala Saleh Alluhaidan, Ali Raza, Sahar A. El-Rahman, Diaa Salama AbdElminaam

“…We have tuned hyperparameters of applied machine learning approaches, and cross-validation is applied to validate performance results. In addition, the complexity of the computation is measured. The proposed research aims to enhance the accuracy measure, and efficiency of identifying manipulated audio content, thereby contributing to the integrity and reliability of digital communications.…”
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MSDNet: A Multi-Scale Feature Representation Network Model for Tunnel Bolt Detection by Xiufeng Wu, Xueli Li, Guangxing Cao, Chao Guo, Wei Chang, Zhao Wang, Shuliang Liu

“…To address these issues, we introduces a novel multi-scale feature extraction detection network (MSDNet) designed to improve tunnel bolt maintenance by reducing false positives and missed detections. …”
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The Scalable Detection and Resolution of Data Clumps Using a Modular Pipeline with ChatGPT by Nils Baumgartner, Padma Iyenghar, Timo Schoemaker, Elke Pulvermüller

“…This paper explores a modular pipeline architecture that integrates ChatGPT, a Large Language Model (LLM), to automate the detection and refactoring of data clumps—a prevalent type of code smell that complicates software maintainability. …”
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InvMOE: MOEs Based Invariant Representation Learning for Fault Detection in Converter Stations by Hao Sun, Shaosen Li, Hao Li, Jianxiang Huang, Zhuqiao Qiao, Jialei Wang, Xincui Tian

“…Converter stations are pivotal in high-voltage direct current (HVDC) systems, enabling power conversion between an alternating current (AC) and a direct current (DC) while ensuring efficient and stable energy transmission. Fault detection in converter stations is crucial for maintaining their reliability and operational safety. …”
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FM-Net: Frequency-Aware Masked-Attention Network for Infrared Small Target Detection by Yongxian Liu, Zaiping Lin, Boyang Li, Ting Liu, Wei An

“…Infrared small target detection (IRSTD) aims to locate and separate targets from complex backgrounds. …”
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Radio Frequency Interference Detection Using Swin Transformer Embedding U2-Net by Shengdi Chen, Bo Liang

“…The main encoder enhances the feature representation through the efficient multiscale attention (EMA) mechanism, reorganizes the channel information, captures pixel-level relationships, and improves the detection accuracy in complex backgrounds. …”
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A novel feature extractor based on constrained cross network for detecting sleep state by Chenlei Tian, Fei Song

“…Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. …”
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DSF-YOLO for weld defect detection in X-ray images with dynamic staged fusion by Meng Zhang, Yanzhu Hu, Binbin Xu, Lisha Luo, Song Wang

“…These results establish DSF-YOLO as an efficient and accurate solution addressing critical challenges in industrial weld defect detection with significant practical value.…”
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Anomaly detection method for cyber physical power system based on bilateral data fusion by Tianlei Zang, Shijun Wang, Chuangzhi Li, Yunfei Liu, Yujian Xiao, Zian Wang, Xueying Yu

“…It is a challenge to fully quantify the complex characteristics of CPPS. A cyber-physical bilateral data-driven composite model is proposed in this paper to achieve efficient and accurate anomaly detection of CPPS. …”
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Research on insider threat detection based on personalized federated learning and behavior log analysis by Xiaoyun Ye, Faqin Luo, Huangrongbin Cui, Jinlong Wang, Xiaoyun Xiong, Wencui Zhang, Jiawei Yu, Wenhao Zhao

“…While machine learning methods offer certain advantages, they still face challenges in complex data scenarios. This study focuses on the application of Federated Learning in insider threat detection. …”
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Research review on intelligent object detection technology for coal mines based on deep learning by Fan ZHANG, Jiarong ZHANG, Haixing CHENG

“…However, deep learning object detection has a strong dependence on annotated datasets, and there are problems such as poor model interpretability and computational complexity. …”
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SmartRipen: LSTM-GRU feature selection& XGBoost-CNN for fruit ripeness detection by Archana Ganesh Said, Bharti Joshi

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CMCD: A Consistency Model-Based Change Detection Method for Remote Sensing Images by Xiongjie Li, Weiying Xie, Jiaqing Zhang, Yunsong Li

“…We also develop a pruning strategy of skip connections and a top–down feature aggregation module to improve feature utilization efficiency. Extensive experiments demonstrate that CMCD significantly reduces computational complexity and inference time compared to existing diffusion model-based methods. …”
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MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images by Huinan Guo, Congying Sun, Jing Zhang, Wuxia Zhang, Nengshuang Zhang

“…To overcome the limitations of existing fusion methods in terms of complexity and insufficient information utilization, we innovatively propose a Cosine Similarity-based Image Feature Fusion (CSIFF) module and integrate it into a dual-branch YOLOv8 network, constructing a lightweight and efficient target detection network called Multi-Modality YOLO Fusion Network (MMYFNet). …”
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Intelligent back-to-back testing with denoising autoencoder-based fault detection and DBSCAN clustering by Mohammad Abboush, Christoph Knieke, Andreas Rausch

“…The approach is capable of automatically detecting and clustering the faults in an efficient manner considering the noisy conditions. …”
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A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

“…PCSN-Net outperforms various complex algorithms, including EfficientNet, DenseNet, and Inception-ResNet-V2, despite preserving effective training and inference times. …”
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