Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease by Jing Wu, Sebastian M. Waldstein, Alessio Montuoro, Bianca S. Gerendas, Georg Langs, Ursula Schmidt-Erfurth

“…The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. …”
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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…This study introduces an innovative approach for detecting abnormal behavior in real-time during the Hajj pilgrimage, utilizing the advanced capabilities of the YOLOv9 algorithm. …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

“…The suggested strategy outperformed modern fall identification techniques when tested using the labeled KFall database, achieving average precision of 95 percent, 96 percent, as well as 98 percent for Non-Falls, Pre-Falls, as well as detectable fall incidents, correspondingly. The whole assessment proved the algorithmic learning structure's efficacy. …”
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A novel and efficient personalized stress detection technique using a deep learning model by Ulligaddala Srinivasarao, Gopisetty Rathnamma, M. Satish Kumar, Lakshmipathi Anantha, Rakesh Kumar Donthi, T. Jhansi Rani

“…Several limitations occurred, such as higher training time, high time consumption, and limited features utilized to train the model. The proposed novelty of the technique is developed to overcome these issues and provide efficient stress detection. …”
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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

“…In this scenario, condition monitoring of the weld using machine learning algorithms is a remedy to detect the defects instantly. …”
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Feasibility of snapshot testing using wearable sensors to detect cardiorespiratory illness (COVID infection in India) by Olivia K. Botonis, Jonathan Mendley, Shreya Aalla, Nicole C. Veit, Michael Fanton, JongYoon Lee, Vikrant Tripathi, Venkatesh Pandi, Akash Khobragade, Sunil Chaudhary, Amitav Chaudhuri, Vaidyanathan Narayanan, Shuai Xu, Hyoyoung Jeong, John A. Rogers, Arun Jayaraman

“…SHAP values were mapped to visualize feature importance and directionality, yielding engineered features from core temperature, cough, and lung sounds as highly important. …”
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Integrating the landscape scale supports SAR-based detection and assessment of the phenological development at the field level by Johannes Löw, Steven Hill, Insa Otte, Christoph Friedrich, Michael Thiel, Tobias Ullmann, Christopher Conrad

“…Unlike previous approaches that focus on local algorithm optimisation or SAR feature selection, this work integrates two scales: (1) landscape patterns derived from annual distributions of time series metrics (TSMs) and (2) field-level phenology, both linked to growing degree days (GDD). …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…Differing from traditional and often expensive or complex detection methods, our approach utilizes a low-cost antipodal Vivaldi antenna, complemented by a custom-designed defect rate detection system. …”
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CBSNet: An Effective Method for Potato Leaf Disease Classification by Yongdong Chen, Wenfu Liu

“…In addition, the Bat–Lion Algorithm (BLA) is introduced, which combines the Lion algorithm and the bat optimization algorithm and makes the optimization process more adaptive by using the bat algorithm to adjust the gradient direction during the updating process of the Lion algorithm. …”
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Spectral monitoring technology for gas concentrations of multiple target components in oil and gas leakage detection by Zhirong ZHANG, Pengchao CHEN, Yongjun CAI, Wenyou DU, Zhonglin LI, Yuntao PENG, Pengshuai SUN, Bian WU

“…ObjectiveTraditional gas monitoring methods for oil and gas leakage fall short in meeting the growing demands for the safe operation and maintenance of smart pipeline networks, due to factors such as low detection sensitivity levels, short calibration intervals, frequent false alarms, limited ranges of detectable gases, susceptibility to environmental interference, and reliance on charged sensors. …”
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Analyzing social psychological impact on emotional expression through peer communication using crayfish optimization algorithm with deep learning model by Umkalthoom Alzubaidi

“…Finally, the crayfish optimization algorithm (COA) adjusts the VAE model’s hyperparameter values, improving classification. …”
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Optimization of a Navigation System for Autonomous Charging of Intelligent Vehicles Based on the Bidirectional A* Algorithm and YOLOv11n Model by Shengkun Liao, Lei Zhang, Yunli He, Junhui Zhang, Jinxu Sun

“…For precise localization of charging areas and piles, the YOLOv11n model is enhanced with a CAFMFusion mechanism to bridge semantic gaps between shallow and deep features, enabling effective local–global feature fusion and improving detection accuracy. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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High-dimensional outlier detection based on deep belief network and linear one-class SVM by Haoqi LI, Na YING, Chunsheng GUO, Jinhua WANG

“…Aiming at the difficulties in high-dimensional outlier detection at present,an algorithm of high-dimensional outlier detection based on deep belief network and linear one-class SVM was proposed.The algorithm firstly used the deep belief network which had a good performance in the feature extraction to realize the dimensionality reduction of high-dimensional data,and then the outlier detection was achieved based on a one-class SVM with the linear kernel function.High-dimensional data sets in UCI machine learning repository were selected to experiment,result shows that the algorithm has obvious advantages in detection accuracy and computational complexity.Compared with the PCA-SVDD algorithm,the detection accuracy is improved by 4.65%.Compared with the automatic encoder algorithm,its training time and testing time decrease significantly.…”
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Detection method of small size defects on pipeline weld surface based on improved YOLOv7. by Xiangqian Xu, Wenting Hou, Xing Li

“…Firstly, in the feature fusion network of YOLOv7, the detection ability of the algorithm to detect small and medium-sized targets in defect images is enhanced by adding a 160*160 small target detection head. …”
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Improved Dab-Deformable Model for Runway Foreign Object Debris Detection in Airport Optical Images by Yang Cao, Yuming Wang, Yilin Zhu, Rui Yang

“…To address the challenges of small targets and complex backgrounds in the dataset, this paper proposes optimizations and improvements based on the advanced detection network Dab-Deformable. First, this paper introduces a Lightweight Deep-Shallow Feature Fusion algorithm (LDSFF), which integrates a hotspot sensing network and a spatial mapping enhancer aimed at focusing the model on significant regions. …”
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A Vision-Based Method for Detecting the Position of Stacked Goods in Automated Storage and Retrieval Systems by Chuanjun Chen, Junjie Liu, Haonan Yin, Biqing Huang

“…This paper proposes a novel machine vision-based detection algorithm that integrates a pallet surface object detection network (STEGNet) with a box edge detection algorithm. …”
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Lightweight deep neural network for contour detection and extraction of wheat spikes in complex field environments by Xin Xu, Haiyang Zhang, Jiangchuan Lu, Ziyi Guo, Juanjuan Zhang, Jibo Yue, Hongbo Qiao, Xinming Ma

“…Method Building on two-year multi-angle wheat spike imagery, we propose an enhanced YOLOv9-LDS multi-scale object detection framework. The algorithm innovatively constructs a lightweight depthwise separable network (LDSNet) as backbone, balancing computational efficiency and accuracy through channel re-parameterization strategy; incorporates an Efficient Local Attention (ELA) module to build feature enhancement networks, and employs dual-path feature fusion mechanisms to strengthen edge texture responses, significantly improving discrimination of overlapping spikes and complex backgrounds. …”
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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…This model aims to address the problems of small targets, missed detection, and misdetection of UAV viewpoint feature detection targets. …”
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Defect detection method of red globe grapes bunches based on near infrared camera imaging by GAO Sheng

“…Then the sample edges and fruit stalks were removed by the normalized supergreen method and the finding large connected domain algorithm to extract the shape feature parameters such as roundness, rectangularity and external rectangular aspect ratio of the defective part of red globe grapes bunches and fruit edges, respectively. …”
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