Evolution and stability of social learning in animal migration by Thøger Engelund Knudsen, Brian R. MacKenzie, Uffe Høgsbro Thygesen, Patrizio Mariani

“…We identify non-linear critical thresholds in social learning regulating successful migrations. …”
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Transfer learning based hybrid feature learning framework for enhanced skin cancer diagnosis using deep feature integration by Maridu Bhargavi, Sivadi Balakrishna

“…To address these issues, this research proposes the DRMv2Net model, a feature fusion deep learning-based technique that integrates multiple pre-trained convolutional neural networks to enhance skin cancer diagnosis. …”
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Leveraging federated learning for DoS attack detection in IoT networks based on ensemble feature selection and deep learning models by Tasneem Qasem Al-Ghadi, Selvakumar Manickam, I. Dewa Made Widia, Eka Ratri Noor Wulandari, Shankar Karuppayah

“…These findings underscore the significant impact of feature selection on learning performance and provide valuable insights into optimizing deep learning-based DoS detection in IoT networks.…”
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Remote Sensing Image Change Detection Based on Multi-Level Diversity Feature Fusion by Honggang Xie, Wanjie Ma

“…Furthermore, to effectively address the problem of boundary misjudgment in change areas caused by fixed thresholds, an Adaptive Threshold Module is devised to adaptively learn the texture features of change and unchanged regions, enabling the generation of more accurate thresholds for boundary determination, thereby improving the robustness of the algorithm model and alleviating false alarms. …”
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Deep Learning Based DDoS Attack Detection by Xu Ziyi

“…Traditional approaches to detection, based on statistical thresholds and signature-based mechanisms, respectively, can hardly cope with the increasing complexity of such an attack. …”
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Measuring the Intracluster Light Fraction with Machine Learning by Louisa Canepa, Sarah Brough, Francois Lanusse, Mireia Montes, Nina Hatch

“…We then transfer its learning onto real data by fine-tuning with a sample of 101 real clusters with their ICL fraction measured manually using the surface brightness threshold method. …”
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On-Chip Age Estimation Using Machine Learning by Turki Alnuayri, Saqib Khursheed, Daniele Rossi

“…It outperforms the state-of-the-art IC age prediction models even when learning and validating the model with aging and PV.…”
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Première observation d’un comportement de Leaf Swallowing chez des chimpanzés vivant en captivité à la Réserve Africaine de Sigean, France by Nathan Cazelles-Durand, Ulrich Maloueki, Lyna Rachid, Marielle Beltrame, Fanny Juillard, Désiré Musuyu-Muganza

“…This observation of LS behavior in naive chimpanzees supports the theory of a predisposition to the realization of LS with rough leaves, probably by individual learning. We also note the important role of social learning (facilitation and imitation) in the LS behaviour spread within the group. …”
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Dynamic Car-Following Model With Jerk Suppression for Highway Autonomous Driving by Ke Liu, Jing Ma, Edmund M.-K. Lai

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Three Machine Learning Techniques for Melanoma Cancer Detection by Hadi Naghavipour, GholamReza Zandi, Abdulaziz Al-Nahari

“…The application of machine learning technologies for cancer detection purposes are rising due to their ever-increasing accuracy. …”
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Fast QTMT partition decision based on deep learning by Shuang PENG, Xiaodong WANG, Zongju PENG, Fen CHEN

“…Compared with the predecessor standards, versatile video coding (VVC) significantly improves compression efficiency by a quadtree with nested multi-type tree (QTMT) structure but at the expense of extremely high coding complexity.To reduce the coding complexity of VVC, a fast QTMT partition method was proposed based on deep learning.Firstly, an attention-asymmetric convolutional neural network was proposed to predict the probability of partition modes.Then, the fast decision of partition modes based on the threshold was proposed.Finally, the cost of coding performance and time was proposed to obtain the optimal threshold, and the threshold decision method was proposed.Experimental results at different levels show that the proposed method achieves an average time saving of 48.62%/52.93%/62.01% with the negligible BDBR of 1.05%/1.33%/2.38%.Such results demonstrate that the proposed method significantly outperforms other state-of-the-art methods.…”
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Thermal field reconstruction based on weighted dictionary learning by Tianyi Zhang, Wenchang Li, Jinyu Xiao, Jian Liu

“…A low‐dimensional linear model is used to accurately represent the thermal fields. The dictionary learning technology is exploited to train the model and the minimum weighted mean square error evaluation method is incorporated to improve the reconstruction accuracy near the temperature triggering threshold. …”
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Detection of Defects on Metal Surfaces Based on Deep Learning by Onur Cem Han, Uğurhan Kutbay

“…Manual inspections are time-consuming and prone to errors, especially as production scales increase Although Deep Learning and Computer Vision techniques show promise, the large data sizes of datasets created for deep learning and the high training costs of deep learning models lead to negative effects in terms of storage and energy efficiency. …”
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Adjacent Inputs With Different Labels and Hardness in Supervised Learning by Sebastian A. Grillo, Julio Cesar Mello Roman, Jorge Daniel Mello-Roman, Jose Luis Vazquez Noguera, Miguel Garcia-Torres, Federico Divina, Pedro Esteban Gardel Sotomayor

“…An important aspect of the design of effective machine learning algorithms is the complexity analysis of classification problems. …”
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Combination strategy of active learning for hyperspectral images classification by Ying CUI, Kai XU, Zhongjun LU, Shubin LIU, Liguo WANG

“…In order to improve the phenomena of jitter and instability of the traditional active learning single strategy algorithm in selecting the most valuable unlabeled samples.The idea of weighted combination of ensemble learning classifier and proposes a joint selection based on the combination strategy method (ESAL,ensemble strategy active learning) was introduced,the combination of the model was extended to the combination of the strategy so as to achieve the fusion of multiple strategies in a single model and achieve higher stability.By analyzing the classification results of hyperspectral remote sensing images,the ESAL algorithm can save 25.4% of the cost compared with the single strategy algorithm and reduce the jitter frequency to 16.67% when the same accuracy threshold is obtained,and the jitter is obviously improved.ESAL algorithm is out of good stability.…”
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GNSS interference mitigation method based on deep learning by Feiqiang Chen, Feiqiang Chen, Zhe Liu, Zhe Liu, Long Huang, Long Huang, Yuchen Xie, Yuchen Xie, Binbin Ren, Qin Zhou

“…By leveraging a deep learning network model, our method automatically selects the optimal interference mitigation technique based on the specific characteristics of the interference. …”
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Statistical mechanics and machine learning of the α-Rényi ensemble by Andrew Jreissaty, Juan Carrasquilla

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The effect of digital citizenship on the quality learning civic education by Riza Alrakhman, Dasim Budimansyah, Sapriya Sapriya, Rahmat Rahmat

“…The study then presents statistical evidence indicating a significant relationship between digital citizenship and learning quality in civic education, as highlighted by a t count (14,510) surpassing the t table (1.66) with a significance level of 0.000, lower than the 0.05 threshold. …”
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EEG-Based Attention Classification for Enhanced Learning Experience by Madiha Khalid Syed, Hong Wang, Awais Ahmad Siddiqi, Shahnawaz Qureshi, Mohamed Amin Gouda

“…This paper presents a novel EEG-based learning system designed to enhance the efficiency and effectiveness of studying by dynamically adjusting the difficulty level of learning materials based on real-time attention levels. …”
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A Deep Learning Biomimetic Milky Way Compass by Yiting Tao, Michael Lucas, Asanka Perera, Samuel Teague, Timothy McIntyre, Titilayo Ogunwa, Eric Warrant, Javaan Chahl

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