Concrete Crack Detection and Segregation: A Feature Fusion, Crack Isolation, and Explainable AI-Based Approach by Reshma Ahmed Swarna, Muhammad Minoar Hossain, Mst. Rokeya Khatun, Mohammad Motiur Rahman, Arslan Munir

“…This research introduces a novel feature fusion approach that enhances crack detection accuracy and interpretability. …”
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Hybrid Big Bang-Big crunch with cuckoo search for feature selection in credit card fraud detection by Mohd Shukri Ab Yajid, Nilesh Bhosle, Gadug Sudhamsu, Ali Khatibi, Sahil Sharma, Rubal Jeet, R. Sivaranjani, A. Bhowmik, A. Johnson Santhosh

“…After feature selection, classification is performed using Deep Convolutional Neural Networks (DCNN) and Enhanced DCNN (EDCNN) to improve detection accuracy. …”
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Third Ventricle Width Measurements Based on YOLO and Localized Intensity Features by Xiao Zhou, Ao Wan, Xingang Mou, Hongling Gao, Zheng Xue

“…Meanwhile, a depth separable path aggregation module is used to improve the channel sensitivity of the feature fusion. Secondly, to solve the problem of third ventricle segmentation measurement, a third ventricle segmentation algorithm based on local intensity features is proposed, which realizes automatic segmentation measurement of third ventricle by calculating the local intensity features of the region and localization of the multi-angle projection method. …”
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DAF-Net: Dual-Aperture Feature Fusion Network for Aircraft Detection on Complex-Valued SAR Image by Qingbiao Meng, Youming Wu, Yuxi Suo, Tian Miao, Qingyang Ke, Xin Gao, Xian Sun

“…Therefore, we propose a dual-aperture feature fusion network (DAF-Net) designed to improve aircraft detection by mining, enhancing, and fusing features from both full-aperture and subaperture images. …”
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Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang, Xintian Liu

“…Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. …”
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Optimization of Sorghum Spike Recognition Algorithm and Yield Estimation by Mengyao Han, Jian Gao, Cuiqing Wu, Qingliang Cui, Xiangyang Yuan, Shujin Qiu

“…By integrating the GOLD module’s dual-branch multi-scale feature fusion and the LSKA attention mechanism, a lightweight detection model is developed. …”
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The abnormal traffic detection scheme based on PCA and SSH by Zhenhui Wang, Dezhi Han, Ming Li, Han Liu, Mingming Cui

“…At the same time, PCSS also combines feature fusion and SSH to enhance the feature extraction of unclear features data, and effectively improve the detection speed and accuracy. …”
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Automatic detection of non-convulsive seizures: A reduced complexity approach by Tazeem Fatma, Omar Farooq, Yusuf U. Khan, Manjari Tripathi, Priyanka Sharma

“…With the use of only one feature, all of the seizures under test were detected correctly, and hence the median sensitivity and specificity of 100% and 99.21% were achieved respectively.…”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…Existing deep learning-based solutions typically involve designing hierarchical models that capture relevant features from each modality, which are then fused for final classification. …”
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A hybrid deep learning and differential evolution approach for accurate fake news detection by Shailendra Pratap Singh, Naween Kumar, Gyanendra Kumar, Ahamed Shafeeq B.M.

“…The proposed framework integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and attention mechanisms for robust feature extraction and classification. By leveraging DE optimization, the model fine-tunes its parameters for improved convergence and detection performance. …”
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WT-HMFF: Wavelet Transform Convolution and Hierarchical Multi-Scale Feature Fusion Network for Detecting Infrared Small Targets by Siyu Li, Jingsi Huang, Qingwu Duan, Zheng Li

“…Yet, a persistent challenge remains: the lack of high-level semantic information may cause the disappearance of small target features in the network’s deep layers, ultimately impairing detection accuracy. …”
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Detection of mare parturition through balanced multi-scale feature fusion based on improved Libra RCNN. by Buyu Wang, Weijun Duan, Jian Zhao, Dongyi Bai

“…This paper addresses the challenges of manual monitoring of parturition in large-scale equine facilities due to the unpredictability of mare parturition timing, proposing an algorithm for detecting mare parturition through a balanced multi-scale feature fusion based on an improved Libra RCNN. …”
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ADAM-DETR: an intelligent rice disease detection method based on adaptive multi-scale feature fusion by Hanyu Song, Xinyue Huang, Ziqiang Wang, Jianwei Hu, Huasheng Zhang, Hui Yang

“…To address the challenges of insufficient feature extraction and poor multi-scale disease adaptability in existing deep learning approaches under complex field environments, this study proposes ADAM-DETR, a rice disease detection algorithm based on improved RT-DETR. …”
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A Deep Learning-Driven CAD for Breast Cancer Detection via Thermograms: A Compact Multi-Architecture Feature Strategy by Omneya Attallah

“…Features from all layers of the three CNNs are subsequently incorporated, and the Minimum Redundancy Maximum Relevance (MRMR) algorithm is utilized to determine the most prominent features. …”
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Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by Wafiq Azizah, Soffiana Agustin

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Cervical Cell Nuclear Segmentation Method Based on Optimized MSER Algorithm by HE Yong jun, ZHANG Xue yuan, SHAO Hui li, DING Bo

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DFDA-AD: An Approach with Dual Feature Extraction Architecture and Dual Attention Mechanism for Image Anomaly Detection by Babak Masoudi

“…Two attention mechanisms are improved and developed in this paper, which provide more important feature maps for clustering by K-means algorithm. …”
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Image small target detection in complex traffic scenes based on Yolov8 multiscale feature fusion by Xuguang Chai, Meizhi Zhao, Jing Li, Junwu Li

“…Addressing the challenging issues in small target detection within complex traffic scenes, such as scale variation, complex background noise, and the problems of missed and false detections, this paper introduces a Multi-Scale Feature Fusion YOLOv8 (MSFF-YOLOv8) approach. …”
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Enhanced Edge Feature Fusion and Visual State Space for Precise Detection of Switch Tip Close Fitting by Chang Zhengtang, Lan Xiangui, Lai Yihui

“…To address this, we propose DU-Net, an improved image segmentation and detection algorithm based on the U-Net model. DU-Net integrates edge feature enhancement and visual state space to accurately segment tracks in rail transit switch images and detect the close-fitting degree between the basic track and switch tip. …”
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