Infrared Small Target Detection Based on Approximate Background Regularization and Bimodal Slice Based Graph Constraints by Xiaoling Ge, Zipeng Fu, Xuelian Yu, Weixian Qian, Kan Ren, Minjie Wan, Guohua Gu

“…Experimental results show that the proposed method outperforms state-of-the-art approaches in both detection performance and efficiency while demonstrating greater robustness in complex scenarios.…”
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FD-YOLO11: A Feature-Enhanced Deep Learning Model for Steel Surface Defect Detection by Zichen Dang, Xingshuo Wang

“…However, the existing methods struggle to balance accuracy and efficiency, especially in complex defect environments, where significant challenges persist. …”
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Improved cohesin HiChIP protocol and bioinformatic analysis for robust detection of chromatin loops and stripes by Karolina Buka, Zofia Parteka-Tojek, Abhishek Agarwal, Michał Denkiewicz, Sevastianos Korsak, Mateusz Chiliński, Krzysztof H. Banecki, Dariusz Plewczynski

“…Using comprehensive bioinformatic analysis, we show that a dual chromatin fixation method compared to the standard formaldehyde-only method, results in a substantially better signal-to-noise ratio, increased ChIP efficiency and improved detection of chromatin loops and architectural stripes. …”
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Research on Lightweight Open-Pit Mine Driving Obstacle Detection Algorithm Based on Improved YOLOv8s by Bo Xu, Wubin Xu, Bing Li, Hanwen Zhang, Yuanbin Xiao, Weixin Zhou

“…Improving the accuracy and speed of obstacle detection during driving is of great significance to ensuring the safety of mine automation construction and improving the efficiency of overall unmanned operations. …”
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Automated lumbar intervertebral disc identification and herniation detection in MR images using cascade CNN architecture by Md Abu Sayed, Ashiqur Rahman, Sadman Mohammad Nasif, Sudipto Halder, Akram Hossain, Hasan Ahmed, Muhammad Abdul Kadir

“…This study aims to develop an automated, accurate, and efficient system for the detection and classification of lumbar intervertebral disc herniation using deep learning models applied to axial and sagittal MR images. …”
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A Cascaded Ensemble Framework Using BERT and Graph Features for Emotion Detection From English Poetry by Praveen K. Kazipeta, Venkatrama Phani Kumar Sistla, Venkata Krishna Kishore Kolli

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YOLOv8-DBW: An Improved YOLOv8-Based Algorithm for Maize Leaf Diseases and Pests Detection by Xiang Gan, Shukun Cao, Jin Wang, Yu Wang, Xu Hou

“…To solve the challenges of low detection accuracy of maize pests and diseases, complex detection models, and difficulty in deployment on mobile or embedded devices, an improved YOLOv8 algorithm was proposed. …”
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Research on Ship Feature Recognition and Tracking Method Based on Long-line Array Single-photon LiDAR by Ziqiang PENG, Han WANG, Ruikai XUE, Xiaokai SHE, Genghua HUANG

“…Owing to the inconsistency between the characteristics of surface ships and ground target, and the lack of relevant data sets, the current commonly used fitting methods cannot effectively perceive surface target characteristics. In this paper, an efficient target tracking method for ships is proposed based on the characteristics of single-photon point clouds and long-distance target detection. …”
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MAH-YOLO: an enhanced YOLOv8n framework for loess landslide detection with multi-attention mechanisms by Yuan Liang, Zhe Chen, Zhengbo Yu, Zhong Wang, Qingyun Ji, Ziqiong He, Dongsheng Zhong, Zhongchang Sun, Huadong Guo

“…Additionally, MAH-YOLO, a low complexity model with only 3.35M parameters and 16.1G FLOPs was used, balancing efficiency and accuracy. …”
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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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FGA-Corn: an integrated system for precision pesticide application in center leaf areas using deep learning vision by Zhongqiang Song, Zhongqiang Song, Wenqiang Li, Xuehang Song, Shun Li

“…The third part is the GMA-YOLOv8 detection algorithm for center leaf areas. Building on the YOLOv8n framework, a more efficient GHG2S backbone generated by HGNetV2 enhanced with GhostConv and SimAM is proposed for feature extraction. …”
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A Lightweight Citrus Ripeness Detection Algorithm Based on Visual Saliency Priors and Improved RT-DETR by Yutong Huang, Xianyao Wang, Xinyao Liu, Liping Cai, Xuefei Feng, Xiaoyan Chen

“…However, accurately and efficiently detecting citrus ripeness in complex orchard environments for selective robotic harvesting remains a challenge. …”
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Improving Fire and Smoke Detection with You Only Look Once 11 and Multi-Scale Convolutional Attention by Yuxuan Li, Lisha Nie, Fangrong Zhou, Yun Liu, Haoyu Fu, Nan Chen, Qinling Dai, Leiguang Wang

“…Although challenges remain in handling occluded targets and complex backgrounds, the model exhibits strong robustness and generalization capabilities, maintaining efficient detection performance in complicated environments.…”
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TCCDNet: A Multimodal Pedestrian Detection Network Integrating Cross-Modal Complementarity with Deep Feature Fusion by Shipeng Han, Chaowen Chai, Min Hu, Yanni Wang, Teng Jiao, Jianqi Wang, Hao Lv

“…Multimodal pedestrian detection has garnered significant attention due to its potential applications in complex scenarios. …”
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Vision transformer-enhanced thermal anomaly detection in building facades through fusion of thermal and visible imagery by Siyu Zheng, Jiaxin Zhang, Rui Zu, Yunqin Li

“…The experimental outcomes reveal that our methodology, with an F1 score of 0.847, markedly surpasses traditional thermal imaging (F1 score of 0.466), showcasing its potential for precise anomaly detection in architectural contexts. This validates the method as a more robust and efficient solution for structural evaluation, promising to elevate the quality of architectural inspections and maintenance.…”
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A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm by Deepshikha Kumari, Prashant Pranav, Abhinav Sinha, Sandip Dutta

“…Key performance metrics were analysed to assess the model’s effectiveness in detecting malicious activities in complex network traffic patterns. …”
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DAM-Faster RCNN: few-shot defect detection method for wood based on dual attention mechanism by Xingyu Tong, Zhihong Liang, Mingming Qin, Fangrong Liu, Jiayu Yang, Hengjiang Xiao, Wei Dai

“…Experimental results show that the proposed method achieves state-of-the-art performance on the PASCAL VOC and FSOD datasets, particularly in the identification of 17 types of wood defects, where AP50 and AP75 are improved by 25% and 7.9%, respectively, validating the significant advantages of the proposed DAM mechanism under few-shot and complex background conditions. The findings of this study provide practical technical references for intelligent and efficient few-shot detection in real-world wood quality inspection tasks.…”
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Analysis of VAE-LSTM Performance in Detecting Anomalies in Average Daily Temperature Data in Jakarta 2000-2023 by INDRI RAMDANI, YENNI ANGRAINI, INDAHWATI INDAHWATI

“…This study contributes to climate research by providing evidence of the effectiveness of deep learning-based hybrid models in detecting complex and context-sensitive temperature anomalies.…”
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Real-time Detection Algorithm of Expanded Feed Image on the Water Surface Based on Improved YOLOv11 by ZHOU Xiushan, WEN Luting, JIE Baifei, ZHENG Haifeng, WU Qiqi, LI Kene, LIANG Junneng, LI Yijian, WEN Jiayan, JIANG Linyuan

“…These improvements showed the effectiveness of the YOLOv11-AP2S model in detecting floating extruded feed particles in complex environments. …”
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WTDBNet: A Wavelet Transform-Based Dual-Stream Backbone Network for Fine-Grained Ship Detection by Wei Cao, Xinyu Zhao, Hongqi Wang, Yuxin Hu

“…Fine-grained ship detection tasks require models to accurately classify fine-grained categories and precisely localize them within complex backgrounds, relying on detailed features. …”
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