A cascaded autoencoder unmixing network for Hyperspectral anomaly detection by Kun Li, Yingqian Wang, Qiang Ling, Yaoming Cai, Yao Qin

“…Most existing methods detect sub-pixel targets in abundance space by spectral unmixing. …”
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Biopolymer-Modified Carbon Paste Electrode for the Electrochemical Detection of Pb(II) in Water by Ousama Ifguis, Abdelaziz Moutcine, Charaf Laghlimi, Younes Ziat, Rachid Bouhdadi, Abdelilah Chtaini, Amine Moubarik, Mohamed Mbarki

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INTEGRATING CNN AND DICTIONARY MECHANISMS FOR EFFECTIVE LOOP CLOSURE DETECTION by Ayda Mohammed Sharif, Sadegh Abdollah Aminifar

“… Loop closure detection (LCD) remains a critical challenge in visual Simultaneous Localization and Mapping (SLAM), particularly in environments with repetitive structures or sparse textures where traditional methods suffer from perceptual aliasing and computational inefficiency. …”
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Research on SBMPC Algorithm for Path Planning of Rescue and Detection Robot by Lin-Lin Wang, Li-Xin Pan

“…The optimum solution of path planning is obtained from candidate solutions through continuous moving optimization of the defined cost function. The effects of the three sampling methods (viz., uniform sampling, Halton’s sampling, and CVT  sampling) on path planning performance are compared in simulations. …”
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Current Techniques for Detecting Sentinel Lymph Nodes in Vulvar Cancer by Sh. Kh. Gantsev, O. N. Lipatov, K. V. Menshikov

“…Detection of sentinel lymph nodes in vulvar cancer is an effective method of planning for the scope of the surgery. …”
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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Abstract With the rapid development of the global financial market, the problem of financial fraud is becoming more and more serious, which brings huge economic losses to the market, consumers and investors and threatens the stability of the financial system. Traditional fraud detection methods based on rules and statistical analysis are difficult to deal with increasingly complex and evolving fraud methods, and there are problems such as poor adaptability and high false alarm rate. …”
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Research Progress in the Detection of Mycotoxins in Cereals and Their Products by Vibrational Spectroscopy by Jihong Deng, Mingxing Zhao, Hui Jiang

“…Researchers have explored various traditional detection methods to address this concern. However, as grain consumption becomes increasingly time-sensitive and dynamic, traditional approaches face growing limitations. …”
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SDN Anomalous Traffic Detection Based on Temporal Convolutional Network by Ziyi Wang, Zhenyu Guan, Xu Liu, Caixia Li, Xuan Sun, Jun Li

“…In response to these challenges, we propose a Temporal Convolutional Network (TCN)-based anomalous traffic detection method for SDN. Taking the packet length sequence as the core feature, the long-term temporal dependency in the traffic data is effectively captured by causal convolution and dilation convolution operations of the TCN model, combined with the residual connection mechanism to optimize the gradient propagation and improve the stability of the model training. …”
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Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection by Alymzhan Toleu, Gulmira Tolegen, Rustam Mussabayev, Alexander Krassovitskiy, Bagashar Zhumazhanov

“…., influence speaker change detection (SCD) performance. The analysis is conducted using two unsupervised methods: Bayesian information criterion with Gaussian mixture model (BIC-GMM), a model-based approach, and Kullback-Leibler divergence with Gaussian Mixture Model (KL-GMM), a metric-based approach. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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A road lane detection approach based on reformer model by Dan Li, Zan Yang, Wei Nai, Yidan Xing, Ziyu Chen

“…At present, road lane detection methods based on Transformer model are currently considered to be most effective and accurate; however, Transformer model-based road lane detection methods still have their own drawbacks, like high computational complexity of attention mechanisms and defects in activation function and loss functions. …”
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Automatic Registration and Error Detection of Multiple Slices Using Landmarks by Hans Frimmel, Lars Egevad, Christer Busch, Ewert Bengtsson

“…This leads to severe registration problems. In this paper, a method for automatic registration and error detection of slices using landmark needles has been developed. …”
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Robust UAV Target Tracking Algorithm Based on Saliency Detection by Hanqing Wu, Weihua Wang, Gao Chen, Xin Li

“…In response to this problem, this paper proposes a robust UAV target tracking algorithm based on saliency detection (SDBCF). Using saliency detection methods, the DCF tracker is optimized in three aspects to enhance the robustness of the tracker in complex scenes: feature fusion, filter-model construct, and scale-estimation methods improve. …”
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Unsupervised Salient Object Detection by Aggregating Multi-Level Cues by Chenxing Xia, Hanling Zhang

“…In this paper, we present a novel method to detect salient object based on multi-level cues. …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…Abstract DETR (DEtection TRansformer) is a CV model for object detection that replaces traditional complex methods with a Transformer architecture, and has achieved significant improvement over previous methods, particularly in handling small and medium-sized objects. …”
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Improved Crack Detection and Recognition Based on Convolutional Neural Network by Keqin Chen, Amit Yadav, Asif Khan, Yixin Meng, Kun Zhu

“…Improved crack detection based on convolutional neural networks can automatically detect whether an image contains cracks and mark the location of the cracks, which can greatly improve the monitoring efficiency. …”
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Microblog Sentiment Orientation Detection Using User Interactive Relationship by Liang Wang, Mei Wang, Xinying Guo, Xuebin Qin

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Saliency Detection via Fusing Color Contrast and Hash Fingerprint by Yin Lv, Xuanrui Zhang, Yong Wang

“…This study proposes a simple and effective saliency detection method combining color contrast and hash fingerprint. …”
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AI-driven epidemic intelligence: the future of outbreak detection and response by Jasleen Kaur, Jasleen Kaur, Zahid Ahmad Butt

“…The growing frequency of emerging infectious diseases highlights the urgency for more rapid and accurate surveillance methods. This perspective proposes a forward-looking conceptual framework for AI-driven epidemic intelligence, emphasizing the transformative potential of integrating large language models (LLMs), natural language processing (NLP), and optimization-based resource allocation strategies. …”
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An Ensemble-Based Approach for Detecting Clickbait in Indonesian Online Media by Sandy Kurniawan, Adhe Setya Pramayoga, Yeva Fadhilah Ashari

“…These findings highlight the effectiveness of ensemble learning in enhancing clickbait detection performance and suggest potential for further optimization in model selection and integration strategies.…”
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