FP-YOLOv8: Surface Defect Detection Algorithm for Brake Pipe Ends Based on Improved YOLOv8n by Ke Rao, Fengxia Zhao, Tianyu Shi

“…To address the limitations of existing deep learning-based algorithms in detecting surface defects on brake pipe ends, a novel lightweight detection algorithm, FP-YOLOv8, is proposed. …”
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MSPB-YOLO: High-Precision Detection Algorithm of Multi-Site Pepper Blight Disease Based on Improved YOLOv8 by Xiaodong Zheng, Zichun Shao, Yile Chen, Hui Zeng, Junming Chen

“…Additionally, the introduction of the RepGFPN network structure enhances the model’s capability for multi-scale feature fusion, resulting in a marked improvement in multi-target detection accuracy. …”
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EDGE DETECTION TECHNIQUE BASED ON BILATERAL FILTERING AND ITERATIVE THRESHOLD SELECTION ALGORITHM AND TRANSFER LEARNING FOR TRAFFIC SIGN RECOGNITION by Milind PARSE, Dhanya PRAMOD

“…The sign edge is a helpful feature for the recognition of traffic signs. A novel traffic sign edge detection algorithm is introduced based on bilateral filtering with adaptive thresholding and varying aperture size that effectively detects the edges from such noisy images. …”
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URT-YOLOv11: A Large Receptive Field Algorithm for Detecting Tomato Ripening Under Different Field Conditions by Di Mu, Yuping Guou, Wei Wang, Ran Peng, Chunjie Guo, Francesco Marinello, Yingjie Xie, Qiang Huang

“…These factors often hinder accurate feature extraction, leading to recognition errors and reduced computational efficiency. …”
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A Method of Fatigue Driving State Detection Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei

“…Current domestic and overseas fatigue recognition algorithms are implemented using fatigue features which are mostly singular and man-made. …”
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Machine Learning-based for Automatic Detection of Corn-Plant Diseases Using Image Processing by Geofrey Prudence Baitu, Y. Benal Öztekin, Omsalma Alsadig Adam Gadalla, Khaled Adil Dawood Idress

“…In this study, four traditional machine learning algorithms were applied to detect diseased maize leaves (common rust and gray leaf spot) and healthy maize leaves. …”
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Enhanced pulmonary nodule detection using a transformer framework with dual fusion and gated mechanism by Kelei Sun, Yihang Wang, Huaping Zhou

“…Existing studies have proposed various enhancement algorithms tailored to pulmonary nodules, but small-sized nodules are still prone to false detections, making accurate detection challenging. …”
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A Welding Defect Detection Model Based on Hybrid-Enhanced Multi-Granularity Spatiotemporal Representation Learning by Chenbo Shi, Shaojia Yan, Lei Wang, Changsheng Zhu, Yue Yu, Xiangteng Zang, Aiping Liu, Chun Zhang, Xiaobing Feng

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Lightweight malicious domain name detection model based on separable convolution by Luhui YANG, Huiwen BAI, Guangjie LIU, Yuewei DAI

“…The application of artificial intelligence in the detection of malicious domain names needs to consider both accuracy and calculation speed,which can make it closer to the actual application.Based on the above considerations,a lightweight malicious domain name detection model based on separable convolution was proposed.The model uses a separable convolution structure.It first applies depthwise convolution on every input channel,and then performs pointwise convolution on all output channels.This can effectively reduce the parameters of convolution process without impacting the effectiveness of convolution feature extraction,and realize faster convolution process while keeping high accuracy.To improve the detection accuracy considering the imbalance of the number and difficulty of positive and negative samples,a focal loss function was introduced in the training process of the model.The proposed algorithm was compared with three typical deep-learning-based detection models on a public data set.Experimental results denote that the proposed algorithm achieves detection accuracy close to the state-of-the-art model,and can significantly improve model inference speed on CPU.…”
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Multimodal anomaly detection in complex environments using video and audio fusion by Yuanyuan Wang, Yijie Zhao, Yanhua Huo, Yiping Lu

“…Abstract Due to complex environmental conditions and varying noise levels, traditional models are limited in their effectiveness for detecting anomalies in video sequences. Aiming at the challenges of accuracy, robustness, and real-time processing requirements in the field of image and video processing, this study proposes an anomaly detection and recognition algorithm for video image data based on deep learning. …”
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An enhanced YOLOv8 model for accurate detection of solid floating waste by Juxing Di, Kaikai Xi, Yang Yang

“…The new model optimizes the feature fusion strategy in the neck, constructing a refined “160-80-40-20” multiscale detection frame work. …”
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Research on a Bone Stick Fragment Stitching Method Based on Improved Corner Detection by Jiahuan Liu, Huiqin Wang, Rui Liu, Ke Wang, Zhan Wang, Ting Wang

“…Then, the broken edge features are enhanced by combining multi-scale and multi-stage corner detection, as well as a double screening mechanism of local template and corner density analysis. …”
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Exposed conductor detection of 10 kV distribution line based on improved YOLOv8 by Qiwen JING, Sipeng HAO, Siyuan LI

“…The algorithm replaces the original convolution with omni-dimensional dynamic convolution in the backbone network, enhancing the features of exposed conductors through multi-dimensional feature extraction. …”
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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Researchers utilizing a hybrid feature extraction method such as Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) followed by metaheuristic feature selection algorithms as Harmonic Search (HS), Dragonfly Algorithm (DFA), Elephant Herding Algorithm (EHA). …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…This method combines weakly supervised learning with energy function optimization to raise the efficiency of image feature annotation in object detection models. Besides, to raise the robustness and accuracy of target tracking algorithms in complex environments, an improved particle filter tracking method based on accelerated robust feature matching is proposed. …”
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A Context-Aware Doorway Alignment and Depth Estimation Algorithm for Assistive Wheelchairs by Shanelle Tennekoon, Nushara Wedasingha, Anuradhi Welhenge, Nimsiri Abhayasinghe, Iain Murray

“…These challenges highlight a pressing need for intelligent doorway detection algorithm for assistive wheelchairs that go beyond traditional object detection. …”
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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…This article addresses the issues of missed and false detections in existing aircraft target fine-grained recognition algorithms for remote sensing images by proposing an improved algorithm based on YOLOv8, called FD-YOLOv8 (Focus Detail-YOLOv8). …”
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ATBHC-YOLO: aggregate transformer and bidirectional hybrid convolution for small object detection by Dandan Liao, Jianxun Zhang, Ye Tao, Xie Jin

“…We propose a new algorithm for detecting small objects in UAV images, called ATBHC-YOLO. …”
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A Decision Support System For Early Stage Parkinson's Diagnosis from EEG Data Using Symbolic Mutual Information and KAC Features by Nurhan Gürsel Özmen, Neslihan Baki

“…Therefore, in this study, an efficient PD detection method from EEG data by using a new set of features is searched. …”
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Intelligent intrusion detection system based on crowd search optimization for attack classification in network security by Chetan Gupta, Amit Kumar, Neelesh Kumar Jain

“…In comparison to the various state-of-the-art classifiers, the CSO method was applied to the NSL-KDD dataset and the ROSPaCe dataset for the detection of the attacks. In the proposed work, we have used a random forest technique to perform feature selection (FS) to improve the effectiveness and efficiency of intrusion detection. …”
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