YOLO-RDM: Innovative Detection Methods for Eggplants and Stems in Complex Natural Environment by Qin Liu, Zhibin Zhou, Lu Xiong, Meilian Lu, Jingwen Ouyang

“…Next, the DD-Head structure reparameterization detection head module is integrated, effectively merging deep and shallow information while retaining small-scale target feature information to improve detection accuracy. …”
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Data mining approach in detecting inaccurate financial statements in government-owned enterprises by Amra Gadžo, Mirza Suljić, Adisa Jusufović, Slađana Filipović, Erna Suljić

“…The study aims to assess the capability of various data mining techniques in detecting inaccurate financial statements of government-owned enterprises operating in the Federation of Bosnia and Herzegovina (FBiH). …”
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Real-Time Resonance Detection and Active Damping in Energy Recovery Railways Applications by Giovanni Marini, Alessandro Lidozzi, Marco di Benedetto, M. Moranchel Perez, Luca Solero

“…Thanks to the HIL, the complete catenary system has been modeled according to the real data provided by the train operator. The control algorithm and the related control board have the same structure as the architecture used in the field. …”
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Eco-friendly and ultra-sensitive electrochemical sensor for sertraline detection in pharmaceuticals and plasma by Ramy E. El-Bahnasawy, Hany A. Batakoushy, Hytham M. Ahmed

“…The modified electrode exhibited enhanced electron transfer kinetics, exhibiting ultra-sensitive SRT detection. According to ICH guidelines, Differential pulse voltammetry (DPV) has been used to estimate the limit of detection (LOD) for SRT, with concentrations ranging from 0.5 µM to 30.0 µM. …”
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MDIGCNet: Multidirectional Information-Guided Contextual Network for Infrared Small Target Detection by Luping Zhang, Junhai Luo, Yian Huang, Fengyi Wu, Xingye Cui, Zhenming Peng

“…Experimental results on public datasets NUDT-SIRST, IRSTD-1k, and SIRST-Aug demonstrate that our algorithm outperforms other state-of-the-art methods in detection performance.…”
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Plastic water bottle detection model using computer vision in aquatic environments by Andrew Heller, Matthew Jacobs, Gilberto Acosta-González, Anna Basola, Jessica Beck, Wesley Garnes, Jarelys A. Hernández Molina, Alanso Johnson, Rebecca Kiriazes, Melissa Lenczewski, Ellen O’Brien, Grace Pooley Deans, Rhea Roxy, Blaise Trapani, Jason H. Davison

“…By using a combination of several publicly available labeled trash and plastic bottle image datasets, the model was trained to achieve high performance with the YOLOv8 object detection model. This was paired with the Norfair object tracking library and a novel post-processing algorithm to filter out false positives. …”
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ASHM-YOLOv9: A Detection Model for Strawberry in Greenhouses at Multiple Stages by Yan Mo, Shaowei Bai, Wei Chen

“…We propose an improved multistage identification model for strawberry based on the YOLOv9 algorithm—the ASHM-YOLOv9 model. The original YOLOv9 showed limitations in detecting strawberries at different growth stages, particularly lower precision in identifying occluded fruits and immature stages. …”
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Pear Fruit Detection Model in Natural Environment Based on Lightweight Transformer Architecture by Zheng Huang, Xiuhua Zhang, Hongsen Wang, Huajie Wei, Yi Zhang, Guihong Zhou

“…The comparison test between RT-DETR and YOLOv5m, YOLOv7, YOLOv8m and YOLOv10m, Deformable-DETR models shows that RT-DETR can achieve a good balance in terms of model lightweight and recognition accuracy compared with other models, and comprehensively exceed the detection accuracy of the current advanced YOLOv10 algorithm, which can realize the rapid detection of Xinli No. 7 fruit. …”
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DCW-YOLO: An Improved Method for Surface Damage Detection of Wind Turbine Blades by Li Zou, Anqi Chen, Chunzi Li, Xinhua Yang, Yibo Sun

“…In light of these challenges, a novel model named DCW-YOLO for surface damage detection of WTBs is proposed in this research, which leverages image data collected by unmanned aerial vehicles (UAVs) and the YOLOv8 algorithm for image analysis. …”
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YOLO-Ginseng: a detection method for ginseng fruit in natural agricultural environment by Zhedong Xie, Zhuang Yang, Chao Li, Zhen Zhang, Jiazhuo Jiang, Hongyu Guo

“…Its unique structure enables the interactive processing of cross-window feature information, expanding the deep perception field of the network while effectively preserving important weight information. This addresses the detection challenges caused by occlusion or overlapping of ginseng fruits, significantly reducing the overall missed detection rate and improving the long-distance detection performance of ginseng fruits; Secondly, in order to maintain the balance between YOLO-Ginseng detection precision and speed, this study employs a mature channel pruning algorithm to compress the model.ResultsThe experimental results demonstrate that the compressed YOLO-Ginseng achieves an average precision of 95.6%, which is a 2.4% improvement compared to YOLOv5s and only a 0.2% decrease compared to the uncompressed version. …”
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Deep learning for smartphone-aided detection system of Helicobacter Pylori in gastric biopsy by Guanmeng Gao, Zihan Wei, Fei Pei, Yajie Du, Beiying Liu

“…Furthermore, the real-time microscopic field, smartphone and AI algorithm were connected through 5G networks and the AI results were sent back to the smartphone for confirmation by the pathologists. …”
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U-Sodar: Noncontact Vital Sign Detection Technology Based on Ultrasonic Radar by Shuaiming HUANG, Xiaohua ZHU, Wubin WANG, Heng ZHAO, Hong HONG

“…To address these challenges, this paper introduces a noncontact vital signal collection device using Ultrasonic radar (U-Sodar), including a set of hardware based on a three-transmitter four-receiver Multiple Input Multiple Output (MIMO) architecture and a set of signal processing algorithms. The U-Sodar local oscillator uses frequency division technology with low phase noise and high detection accuracy; the receiver employs front-end direct sampling technology to simplify the involved structure and effectively reduce external noise, and the transmitter uses an adjustable PWM direct drive to emit various ultrasonic waveforms, possessing software-defined ultrasonic system characteristics. …”
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Lightweight hybrid transformers-based dyslexia detection using cross-modality data by Abdul Rahaman Wahab Sait, Yazeed Alkhurayyif

“…Traditional dyslexia detection (DD) relies on lengthy, subjective, restricted behavioral evaluations and interviews. …”
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Hybrid CNN-Transformer Model for Accurate Impacted Tooth Detection in Panoramic Radiographs by Deniz Bora Küçük, Andaç Imak, Salih Taha Alperen Özçelik, Adalet Çelebi, Muammer Türkoğlu, Abdulkadir Sengur, Deepika Koundal

“…<b>Methods:</b> The proposed model combines YOLO (You Only Look Once) and RT-DETR (Real-Time Detection Transformer) models to leverage their strengths in real-time object detection and learning long-range dependencies, respectively. …”
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RGB-to-hyperspectral conversion for accessible melanoma detection: A CNN-based approach by Bsharat Sondos Mahmoud, Abouelnour Sana, Ahmed Ragad, Elkhatib Mariam, Gaber Sama, Shehieb Wessam, Arshad Kamran, Assaleh Khaled

“…Through this conversion process, spectral information is improved, enabling a more thorough examination to detect melanoma. Principal component analysis (PCA) aids the machine learning algorithm in differentiating between melanoma and healthy moles in the classification model. …”
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Generative Adversarial and Transformer Network Synergy for Robust Intrusion Detection in IoT Environments by Pardis Sadatian Moghaddam, Ali Vaziri, Sarvenaz Sadat Khatami, Francisco Hernando-Gallego, Diego Martín

“…Additionally, an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm is employed to fine-tune the hyper-parameters of the hybrid model, further enhancing learning stability and detection performance. …”
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Efficient Detection of Microplastics on Edge Devices With Tailored Compiler for TinyML Applications by Alessandro Cerioli, Lorenzo Petrosino, Daniele Sasso, Clement Laroche, Tobias Piechowiak, Luca Pezzarossa, Mario Merone, Luca Vollero, Anna Sabatini

“…The current study aims to train and benchmark AI models tailored for the detection of microplastic in water from scattered signals. …”
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A Rapid Sand Gradation Detection Method Based on Dual-Camera Fusion by Shihao Zhang, Yang Zhang, Song Sun, Xinghai Yuan, Haoxuan Sun, Heng Wang, Yi Yuan, Dan Luo, Chuanyun Xu

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Automatic melanoma detection using an optimized five-stream convolutional neural network by Vida Esmaeili, Mahmood Mohassel Feghhi, Hadi Seyedarabi

“…The simulation results of our proposed method are promising compared to the most relevant state-of-the-art methods for melanoma detection in dermoscopy images. Our proposed method has automatically detected melanoma in 99.8%, 99.9%, 99.62%, and 99.6% of the HAM 10000, ISIC 2024, ISIC 2017, and ISIC 2016 datasets, respectively.…”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

“…Abstract With the increasing demand for precision agriculture, automatic detection of tomato leaf diseases has become a critical technological challenge in smart agriculture. …”
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