LSTM-JSO framework for privacy preserving adaptive intrusion detection in federated IoT networks by Shaymaa E. Sorour, Mohammed Aljaafari, Amany M. Shaker, Ahmed E. Amin

“…The framework dynamically optimizes hyperparameters using the Joint Strategy Optimization (JSO) algorithm, ensuring efficient model adaptation across heterogeneous IoT networks. …”
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Sowing, Monitoring, Detecting: A Possible Solution to Improve the Visibility of Cropmarks in Cultivated Fields by Filippo Materazzi

“…This study explores the integration of UAS-based multispectral remote sensing and targeted agricultural practises to improve cropmark detection in buried archaeological contexts. The research focuses on the Vignale plateau, part of the pre-Roman city of Falerii (Viterbo, Italy), where traditional remote sensing methods face challenges due to complex environmental and archaeological conditions. …”
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Real-time detection of Chinese cabbage seedlings in the field based on YOLO11-CGB by Hang Shi, Hang Shi, Changxi Liu, Changxi Liu, Miao Wu, Miao Wu, Hui Zhang, Hui Zhang, Hang Song, Hang Song, Hao Sun, Hao Sun, Yufei Li, Yufei Li, Jun Hu, Jun Hu

“…The model’s outputs are visualized using a heat map, and an Average Temperature Weight (ATW) metric is introduced to quantify the heat map’s effectiveness.Results and discussionComparative analysis reveals that YOLO11-CGB outperforms established object detection models like Faster R-CNN, YOLOv4, YOLOv5, YOLOv8 and the original YOLO11 in detecting Chinese cabbage seedlings across varied heights, angles, and complex settings. …”
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Cyberattack Detection Systems in Industrial Internet of Things (IIoT) Networks in Big Data Environments by Abdullah Orman

“…Traditional intrusion detection systems (IDSs) often struggle to effectively identify and mitigate complex cyberthreats, such as denial-of-service (DoS) and distributed denial-of-service (DDoS) attacks. …”
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Streamlined Bearing Fault Detection Using Artificial Intelligence in Permanent Magnet Synchronous Motors by Javier de las Morenas, Lidia M. Belmonte, Rafael Morales

“…Permanent magnet synchronous motors (PMSMs) are widely used in industrial applications due to their high efficiency and reliability. However, bearing faults remain a critical issue, necessitating robust fault detection strategies. …”
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Characterising Payload Entropy in Packet Flows—Baseline Entropy Analysis for Network Anomaly Detection by Anthony Kenyon, Lipika Deka, David Elizondo

“…A key technique in early detection is the classification of unusual patterns of network behaviour, often hidden as low-frequency events within complex time-series packet flows. …”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The increasing penetration of renewable energy into power systems has intensified transient power quality (PQ) disturbances, demanding efficient detection and classification methods to enable timely operational decisions. …”
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TomaFDNet: A multiscale focused diffusion-based model for tomato disease detection by Rijun Wang, Rijun Wang, Yesheng Chen, Fulong Liang, Xiangwei Mou, Xiangwei Mou, Guanghao Zhang, Hao Jin

“…Current tomato leaf disease detection methods, however, encounter challenges in extracting multi-scale features, identifying small targets, and mitigating complex background interference. …”
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YOLO-WAS: A Lightweight Apple Target Detection Method Based on Improved YOLO11 by Xinwu Du, Xiaoxuan Zhang, Tingting Li, Xiangyu Chen, Xiufang Yu, Heng Wang

“…To overcome the limitations of existing apple target detection methods, including low recognition accuracy of multi-species apples in complex orchard environments and a complex network architecture that occupies large memory, a lightweight apple recognition model based on the improved YOLO11 model was proposed, named YOLO-WAS model. …”
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Towards precision agriculture tea leaf disease detection using CNNs and image processing by Irfan Sadiq Rahat, Hritwik Ghosh, Suresh Dara, Shashi Kant

“…Our model’s architecture is not just a testament to the sophistication of modern deep learning techniques but also highlights the novelty of applying such complex structures to the challenges of agricultural disease detection. …”
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An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants by Florence Choong Chiao Mei, Bryan Ng Jan Hong

“…However, many detection methods are complex, require high computational power and time to perform the required analysis and focus only on a particular species or strain of the disease. …”
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A Non-Contact AI-Based Approach to Multi-Failure Detection in Avionic Systems by Chengxin Liu, Michele Ferlauto, Haiwen Yuan

“…The increasing electrification and integration of advanced controls in modern aircraft designs have significantly raised the number and complexity of installed printed circuit boards (PCBs), posing new challenges for efficient maintenance and rapid failure detection. …”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

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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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YOLO-SSFA: A Lightweight Real-Time Infrared Detection Method for Small Targets by Yuchi Wang, Minghua Cao, Qing Yang, Yue Zhang, Zexuan Wang

“…Infrared small target detection is crucial for military surveillance and autonomous driving. …”
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Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments by Youlong Weng, Ziang Zhang, Guangzhi Chen, Yaru Zhang, Jiabao Chen, Hongzhan Song

“…In this paper, we propose an efficient solution for real-time radar interference mitigation. …”
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PlantNet: Scalable Convolutional Neural Network for Image-Based Plant Disease Detection by Sinha Anupa, Kumaraswamy Balasubramaniam

“…By leveraging deep learning techniques, PlantNet processes large-scale image datasets to detect disease symptoms with high precision. The model employs transfer learning, utilizing pre-trained networks on vast image repositories before fine-tuning on a specialized plant disease dataset, thereby enhancing feature extraction while minimizing computational complexity. …”
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Defect Detection of Gas Insulation Switch by Infrared Thermography Technology With an Improved Yolo Algorithm by Ma Tianci, Chen Xiangping, Li Bo, Bai Jie

“…However, conventional nondestructive detection methods like ultrasound and X-ray face the challenges in anti-interference capability, cost, and structural complexity. …”
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A lightweight remote sensing image detection model with feature aggregation diffusion network by Xiaohui Cheng, Xukun Wang, Yun Deng, Qiu Lu, Yanping Kang, Jian Tang, Yuanyuan Shi, Junyu Zhao

“…However, existing deep learning models often face challenges in balancing detection accuracy and computational efficiency, especially for small objects in complex scenes. …”
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A hybrid approach using support vector machine rule-based system: detecting cyber threats in internet of things by M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian, Rajkumar Singh Rathore, Mohit Bajaj, Ievgen Zaitsev

“…The security of these network devices and the dependability of IoT networks depend on efficient threat detection. Device heterogeneity, computing resource constraints, and the ever-changing nature of cyber threats are a few of the obstacles that make detecting cyber threats in IoT systems difficult. …”
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