QEDetr: DETR with Query Enhancement for Fine-Grained Object Detection by Chenguang Dong, Shan Jiang, Haijiang Sun, Jiang Li, Zhenglei Yu, Jiasong Wang, Jiacheng Wang

“…Therefore, we propose an oriented fine-grained object detection method based on transformers. First, we combine denoising training and angle coding to propose a baseline DETR-like object detector for oriented object detection. …”
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Object detection model design for tiny road surface damage by Chenguang Wu, Min Ye, Hongwei Li, Jiale Zhang

“…However, existing detection methods generally suffer from insufficient generalization capability, poor detection of tiny damage, and difficulty balancing detection accuracy and computational cost. …”
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Effect of Gold Nanoparticles on Luminescence Enhancement in Antibodies for TORCH Detection by Cuimei Chen, Ping Ding

“…Purposes: To explore the optimization method and application of Au-NP-enhanced luminol––H₂O₂ luminescence system in TORCH (TOX, RV, CMV, HSVI, and HSVII) detection. …”
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AI-Driven Boost in Detection Accuracy for Agricultural Fire Monitoring by Akmalbek Abdusalomov, Sabina Umirzakova, Komil Tashev, Jasur Sevinov, Zavqiddin Temirov, Bahodir Muminov, Abror Buriboev, Lola Safarova Ulmasovna, Cheolwon Lee

“…However, conventional detection methods frequently fall short in accurately identifying small-scale fire outbreaks due to limitations in sensitivity and response speed. …”
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AI-assisted ophthalmic imaging for early detection of neurodegenerative diseases by Hajar Nasir Tukur, Olivier Uwishema, Hatice Akbay, Dalal Sheikhah, Inês Filipa Silva Correia

“…Since early diagnosis is crucial for slowing disease progression and improving patient outcomes, leveraging AI-assisted ophthalmic imaging retinal imaging can enhance detection accuracy and clinical decision-making. Methods This review examines clinical applications of AI in identifying retinal biomarkers associated with neurodegenerative diseases. …”
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Detection and quantification of methane plumes with the MethaneAIR airborne spectrometer by L. Guanter, L. Guanter, J. Warren, M. Omara, A. Chulakadabba, A. Chulakadabba, J. Roger, M. Sargent, J. E. Franklin, S. C. Wofsy, R. Gautam

“…In this work, we present a computationally efficient data processing chain optimized for the detection and quantification of methane plumes with MethaneAIR. …”
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Detection of Electric Network Frequency in Audio Using Multi-HCNet by Yujin Li, Tianliang Lu, Shufan Peng, Chunhao He, Kai Zhao, Gang Yang, Yan Chen

“…With the increasing application of electrical network frequency (ENF) in forensic audio and video analysis, ENF signal detection has emerged as a critical technology. However, high-pass filtering operations commonly employed in modern communication scenarios, while effectively removing infrasound to enhance communication quality at reduced costs, result in a substantial loss of fundamental frequency information, thereby degrading the performance of existing detection methods. …”
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Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…Although state-of-the-art deep learning-based OD methods achieve high detection rates, their large model size and high computational demands often hinder deployment on resource-constrained edge devices. …”
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Research on Fire Detection of Cotton Picker Based on Improved Algorithm by Zhai Shi, Fangwei Wu, Changjie Han, Dongdong Song

“…This study can detect cotton picker fires in real time and provide timely warnings, which provides a new method for the accurate detection of fires during the field operation of cotton pickers.…”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…Most of the previous work concentrated on how to build a deep learning framework to improve the PAD performance by augmenting fingerprint samples, and little attention has been paid to the fundamental difference between live and fake fingerprints to optimize feature extractors. This paper proposes a new fingerprint liveness detection method based on Siamese attention residual convolutional neural network (Res-CNN) that offers an interpretative perspective to this challenge. …”
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High accuracy and octave error immune pitch detection algorithms by M. Dziubiński, B. Kostek

“…In addition, octave error optimized pitch detection algorithm, based on spectral analysis is introduced. …”
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Metric-based learning approach to botnet detection with small samples by Honggang LIN, Junjing ZHU, Lin CHEN

“…Botnets pose a great threat to the Internet, and early detection is crucial for maintaining cybersecurity.However, in the early stages of botnet discovery, obtaining a small number of labeled samples restricts the training of current detection models based on deep learning, leading to poor detection results.To address this issue, a botnet detection method called BT-RN, based on metric learning, was proposed for small sample backgrounds.The task-based meta-learning training strategy was used to optimize the model.The verification set was introduced into the task and the similarity between the verification sample and the training sample feature representation was measured to quickly accumulate experience, thereby reducing the model’s dependence on the labeled sample space.The feature-level attention mechanism was introduced.By calculating the attention coefficients of each dimension in the feature, the feature representation was re-integrated and the importance attention was assigned to optimize the feature representation, thereby reducing the feature sparseness of the deep neural network in small samples.The residual network design pattern was introduced, and the skip link was used to avoid the risk of model degradation and gradient disappearance caused by the deeper network after increasing the feature-level attention mechanism module.…”
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YOLOX-S-TKECB: A Holstein Cow Identification Detection Algorithm by Hongtao Zhang, Li Zheng, Lian Tan, Jiahui Gao, Yiming Luo

“…Therefore, this paper proposes a cow identification method based on YOLOX-S-TKECB. (1) Based on the characteristics of Holstein cows and their breeding practices, we constructed a real-time acquisition and preprocessing platform for two-dimensional Holstein cow images and built a cow identification model based on YOLOX-S-TKECB. (2) Transfer learning was introduced to improve the convergence speed and generalization ability of the cow identification model. (3) The CBAM attention mechanism module was added to enhance the model’s ability to extract features from cow torso patterns. (4) The alignment between the apriori frame and the target size was improved by optimizing the clustering algorithm and the multi-scale feature fusion method, thereby enhancing the performance of object detection at different scales. …”
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Harmonic and interharmonic detection based on adaptive wavelet and improved EWT by KONG Chuirui, CHEN Fengxian, YANG Lingrui, CHE Yukui, YANG Haixian, XIA Wei, GUO Cheng

“…Comparison with empirical mode decomposition （EMD） and particle swarm optimization based variational mode decomposition （PSO-VMD） verifies the superiority of the proposed method in separating harmonics and detecting interharmonics.…”
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Real-time motion detection using dynamic mode decomposition by Marco Mignacca, Simone Brugiapaglia, Jason J. Bramburger

“…Abstract Dynamic mode decomposition (DMD) is a numerical method that seeks to fit time-series data to a linear dynamical system. …”
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MODEL BASED FAULT DETECTION FOR SAFETY MANAGEMENT OF THE INDUSTRIAL PROCESSES by Dumitru POPESCU, Pierre BORNE, Crina TOROUS

“…The variables of these connections are specified from the a-priori knowledge on the process. To detect the process faults, the paper proposes a method based on analytical redundance evaluation and on computing residues, using the measurements collected from the process and on the mathematical models associated to the process. …”
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A new Hybrid Metaheuristic Model for Image Edge Detection by Adil Khalil, Adel Abed Al Wahaab, Ahmed Abbas

“…It was concluded from this study that modifying the parameters of the Canny filter using the proposed dynamic model leads to optimizing the image edge detection processes. Therefore, integrating other algorithms, such as deep learning techniques, is recommended to study the parameters and performance of edge detection operators.…”
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Hierarchical Sampling Representation Detector for Ship Detection in SAR Images by Ming Tong, Shenghua Fan, Jiu Jiang, Chu He

“…Furthermore, experimental results on three authoritative SAR-oriented datasets for ship detection application present the comprehensive performance of our method.…”
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Target Detection in Low Grazing Angle with Adaptive OFDM Radar by Yang Xia, Zhiyong Song, Zaiqi Lu, Hao Wu, Qiang Fu

“…Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. …”
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Feature-adaptive anomaly detection model for onion inspection system by Ziwei Song, Prawit Buayai, Koji Makino, Xiaoyang Mao

“…The VBIM introduces a new feature-adaptive anomaly detection method, which optimizes feature layer weights in a student-teacher anomaly detection model. …”
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