SDD-Net: A Steel Surface Defect Detection Method Based on Contextual Enhancement and Multiscale Feature Fusion by Chao Liang, Zi-Zheng Wang, Xiao-Lin Liu, Peng Zhang, Zhi-Wei Tian, Ru-Liang Qian

“…Secondly, in order to solve the problem that tiny targets in industrial datasets have fuzzy texture and contain few features that are difficult to be detected, a Context Enhancement Module (CEM) is proposed, which effectively complements the contextual information of the small targets and performs multi-scale fusion to enhance the semantic information representation. …”
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ID-insensitive deepfake detection model based on multi-attention mechanism by Yuncan Sheng, Zhengrui Zou, Zongxuan Yu, Mengxue Pang, Wei Ou, Wenbao Han

“…However, existing methods frequently overlook the connection between local details and overall image features, while also failing to address the problem of implicit identity leakage. …”
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A Small Object Detection Algorithm Integrated with ReFPN and Compound Attention Mechanism by ZHAO Yi-ming, WANG Jin-cong, REN Hong-e, ZHAO Long

“…To solve this problem, a feedback-based feature fusion network (ReFPN) for YOLOV4 algorithm was proposed.The original feature layer extracted from the backbone network is used twice to enhance the feature information of small targets and position regression performs more accurately. …”
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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

“…The stitching of bone stick fragments is of great significance for the inheritance of and research into the outstanding traditional culture of the Western Han Dynasty. Focused on the problem that the existing methods have a low bone stick fragment stitching success rate due to their complex edges, this paper proposes a bone stick fragment stitching method based on improved corner detection, which strengthens the features of broken edges and improves the success rate of stitching. …”
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Improved YOLOv7-Tiny for the Detection of Common Rice Leaf Diseases in Smart Agriculture by Fuxu Guo, Jing Li, Xingcheng Liu, Sinuo Chen, Hongze Zhang, Yingli Cao, Songhong Wei

“…This study proposes a multi-size rice leaf disease detection model, YOLOv7-tiny, for fast and accurate detection of rice leaf diseases. …”
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ALPD-Net: a wild licorice detection network based on UAV imagery by Jing Yang, Huaibin Qin, Jianguo Dai, Guoshun Zhang, Miaomiao Xu, Yuan Qin, Jinglong Liu

“…Traditional licorice resource survey methods are unsuitable for complex terrain and do not meet the requirements of large-scale monitoring.MethodsIn order to solve this problem, this study constructs a new dataset of wild licorice that was gathered using Unmanned Aerial Vehicle (UAV) and proposes a novel detection network named ALPD-Net for identifying wild licorice. …”
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StarCD-Net: A Remote Sensing Change Detection Method Combining StarNet and Differential Operators by Caijia Zeng, Xiaorong Xue, Chuanlu Li, Xingbiao Xu, Siyue Zhao, Yifan Xu

“…To address the problem of loss of edge details, we design the Detailed Feature Enhancement (DFE) Module to enhance the feature edges. …”
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Hierarchical Knowledge Transfer: Cross-Layer Distillation for Industrial Anomaly Detection by Junning Xu, Sanxin Jiang

“…There are two problems with traditional knowledge distillation methods in industrial anomaly detection: first, traditional methods mostly use feature alignment between the same layers. …”
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Improved YOLOv8 Object Detection Method for Drone Aerial Images by Zhong Shuai, Wang Liping

“…A new improved YOLOv8 drone aerial image object detection method, referred to as the BDI-YOLO model, is proposed to address the problems of small target object size and blurry feature information in drone aerial images, which can lead to missed and false detections. …”
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Research on Lightweight Small Object Detection Algorithm Based on Context Representation by Li Qiang, Cui Jianghui

“…This framework model consists of three parts: a backbone network, a multi-scale feature representation network, and a detection head. …”
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Multi-scale aware dual path network for face detection in resource-constrained edge computing environment by Qi QI, Yingxin MA, Jingyu WANG, Haifeng SUN, Jianxin LIAO

“…Aiming at the problem that face detectors with complex deep neural structures are difficult to deploy in the resource-constrained edge computing environment,to reduce the resource consumption while maintain the accuracy in complex scenes such as multi-scale face changes,occlusion,blur,and illumination,SDPN(multi-scale aware dual path network) for face detection was proposed.The Face-ResNet (face residual neural network) was improved,and a dual path shallow feature extractor was used to understand the multi-scale information of the image through parallel branches.Then the deep and shallow feature fusion module,a combination of the underlying image information and the high-level semantic feature,was used in conjunction with the multi-scale awareness training strategy to supervise the multi-branch learning discriminating features.The experimental results show that SDPN can extract more diversified features,which effectively improve the accuracy and robustness of face detection while maintaining the efficiency of the model and low inference delay.…”
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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…However, the robustness of existing trackers is still poor when facing complex scenes, such as background clutter, occlusion, camera motion, and scale variations. In response to this problem, this paper proposes a robust UAV target tracking algorithm based on saliency detection (SDBCF). …”
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Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

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A critical review of technical case studies for electricity theft detection in smart grids: A new paradigm based transformative approach by Muhammad Sajid Iqbal, Shoaib Munawar, Muhammad Adnan, Ali Raza, Muhammad Ali Akbar, Amine Bermak

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INVESTIGATION OF THE CAPABILITIES OF ARTIFICIAL NEURAL NETWORKS WHEN CLASSIFYING OBJECTS DYNAMIC FEATURES by Nikita V. Laptev, Olga M. Gerget, Vladislav V. Laptev, Dmitriy Yu. Kolpashchikov

“…Deep neural networks are widely used in the field of object classification. However, the problem of analyzing objects with dynamically changing features remains relevant. …”
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Yolov4 High-Speed Train Wheelset Tread Defect Detection System Based on Multiscale Feature Fusion by Changfan Zhang, Xinliang Hu, Jing He, Na Hou

“…This study aims to solve this problem by proposing a Yolov4-based multiscale feature fusion detection system for high-speed train wheel tread defects. …”
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Research on hybrid intrusion detection based on improved Harris Hawk optimization algorithm by Pengzhen Zhou, Huifu Zhang, Wei Liang

“…Aiming at the problem of low detection accuracy of network traffic data types by traditional intrusion detection methods, we propose an improved Harris Hawk hybrid intrusion detection method to enhance the detection capability. …”
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NMS-KSD: Efficient Knowledge Distillation for Dense Object Detection via Non-Maximum Suppression and Feature Storage by Suho Son, Byung Cheol Song

“…However, directly applying FKD’s knowledge storage mechanism to dense object detectors causes a storage space problem. To address this issue, we propose NMS-KSD, a novel knowledge storage distillation method designed for dense object detection tasks. …”
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RaHFF-Net: Recall-Adjustable Hierarchical Feature Fusion Network for Remote Sensing Image Change Detection by Bin Wang, Kang Zhao, Tong Xiao, Pinle Qin, Jianchao Zeng

“…For complex scenarios (e.g., varying lighting conditions), the diverse shapes and scales of the changed areas is especially vulnerable to cause CD models to suffer from serious missed detections. To address aforementioned problem, we propose a high recall multiscale feature fusion model for RS change interpretation. …”
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Infrared Moving Small Target Detection Based on Spatial–Temporal Feature Fusion Tensor Model by Deyong Lu, Wei An, Haibo Wang, Qiang Ling, Dong Cao, Miao Li, Zaiping Lin

“…In this article, a novel method based on the spatial–temporal feature fusion tensor model is proposed to solve these problems. …”
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