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Development of an exteroceptive sensor suite on unmanned surface vessels for real-time classification of navigational markers

• Authors : Kennedy, Christopher Lloyd; Kennedy, Christopher Lloyd

Subjects: Vehicles, Remotely piloted.; Sensor networks.; Véhicules télécommandés.

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Classification of in-flight fatigue cracks in aircraft structures using acoustic emission and neural networks

• Authors : Rovik, Christopher Lee; Eric v. K. Hill; Frank J. Radosta

Subjects: Acoustic emission testing.; Neural networks (Computer science); Composite materials.

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Scaling Crowdsourced Election Monitoring: Construction and Evaluation of Classification Models for Multilingual and Cross-Domain Classification Settings

• Authors : Magomere, Jabez; Hale, Scott

Subjects: Computer Science - Computation and Language; text

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Dynamic Classification: Leveraging Self-Supervised Classification to Enhance Prediction Performance

• Authors : Zhong, Ziyuan; Zhou, Junyang

Subjects: Computer Science - Machine Learning; Computer Science - Artificial Intelligence; J.0

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Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification

• Authors : Liu, Rong; Liang, Junye; Yang, Jiaqi

Subjects: Computer Science - Computer Vision and Pattern Recognition; text

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Statistical Query Hardness of Multiclass Linear Classification with Random Classification Noise

• Authors : Diakonikolas, Ilias; Ma, Mingchen; Ren, Lisheng

Subjects: Computer Science - Machine Learning; Statistics - Machine Learning; text

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Leveraging explainable AI for early risk prediction and type classification for leukemia : insights using clinical data from Pakistan

• Authors : Shahbaz, Maryam; Basharat, Amna; Yasmin, Rehana

Subjects: journal article

• Source: Leveraging explainable AI for early risk prediction and type classification for leukemia : insights using clinical data from Pakistan

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A reproducibility study on invasion in small pulmonary adenocarcinoma according to the WHO and a modified classification, supported by biomarkers

• Authors : Thunnissen, Erik; Blaauwgeers, Hans; Filipello, Federica

Subjects: dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_being; article; article

• Source: Thunnissen, E, Blaauwgeers, H, Filipello, F, Lissenberg-Witte, B, Minami, Y, Noguchi, M, Quesne, J L, Papotti, M G, Flieder, D B, Pelosi, G, Sansano, I, Berezowska, S, Ryška, A, Brcic, L, Motoi, N,

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Comparative Analysis of Deep Learning Models for Crop Diseases and Pest Classification

• Authors : Vincent Mbandu Ochango; Geoffrey Mariga Wambugu; Aaron Mogeni Oirere

Subjects: Deep learning; Crop Diseases; Pest Classification

• Source: International Journal of Formal Sciences: Current and Future Research Trends; Vol. 22 No. 1 (2024); 1-25; 2790-7945

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Comparative Analysis of Deep Learning Models for Crop Diseases and Pest Classification

• Authors : Vincent Mbandu Ochango; Geoffrey Mariga Wambugu; Aaron Mogeni Oirere

Subjects: Deep learning; Crop Diseases; Pest Classification

• Source: International Journal of Formal Sciences: Current and Future Research Trends; Vol. 22 No. 1 (2024); 1-25; 2790-7945

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