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Applied Science & Technology Full Text (H.W. Wilson)

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Applied Science & Technology Full Text (H.W. Wilson)

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Agricola

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Agricola

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Deep Fuzzy Cognitive Maps for Defect Inspection in Antenna Assembly.

• Authors : Tziolas, T.; Papageorgiou, K.; Feleki, A.

Subjects: DEEP learning; COGNITIVE maps (Psychology); KNOWLEDGE representation (Information theory)

• Source: Procedia Computer Science; 2024, Vol. 232, p97-106, 10p

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Creating saliency maps for video stimuli and comparing with eye movement data.

• Authors : Kasprowski, Pawel; Marczewski, Dawid; Harezlak, Katarzyna

Subjects: EYE movements; DEEP learning; GAZE

• Source: Procedia Computer Science; 2024, Vol. 246, p2922-2932, 11p

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Generation and optimisation of colour-shaded relief maps using neural networks.

• Authors : Chenglin Bian; Shaomei Li; Jingzhen Ma

Subjects: TOPOGRAPHIC maps; RELIEF models; DIGITAL elevation models

• Source: Geocarto International; Jun2024, Vol. 39 Issue 1, p1-20, 20p

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A maps-to-maps approach for simulating urban land expansion based on convolutional long short-term memory neural networks.

• Authors : Zhou, Zihao¹ (AUTHOR); Chen, Yimin¹ (AUTHOR) ; Liu, Xiaoping¹ (AUTHOR)

Subjects: *Maps; Urban growth; Urban land useChina

• Source: International Journal of Geographical Information Science. Mar2024, Vol. 38 Issue 3, p503-526. 24p.

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Agricola

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Detection of Attention Deficit Hyperactivity Disorder based on EEG feature maps and deep learning.

• Authors : Karabiber Cura, Ozlem; Akan, Aydin; Kocaaslan Atli, Sibel

Subjects: ATTENTION-deficit hyperactivity disorder; FEATURE extraction; FEATURE selection

• Source: Biocybernetics & Biomedical Engineering; Jul2024, Vol. 44 Issue 3, p450-460, 11p

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