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En el instante 21 de octubre de 2025, 9:00:36 UTC,
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Añadido recurso Valley Classification using Convolutional Neural Network and a Geomorphons Map a Valley Classification using Convolutional Neural Network and a Geomorphons Map
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| 2 | "author": "J Paredes-Tavares, R Lopez-Farias, SI Valdez, HS | 2 | "author": "J Paredes-Tavares, R Lopez-Farias, SI Valdez, HS | ||
| 3 | Lamphar", | 3 | Lamphar", | ||
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| 62 | "notes": "Geomorphological classification serves as a valuable tool | 62 | "notes": "Geomorphological classification serves as a valuable tool | ||
| 63 | for comprehending the origin and evolution of landscapes, as well as | 63 | for comprehending the origin and evolution of landscapes, as well as | ||
| 64 | for making informed decisions regarding environmental hazard | 64 | for making informed decisions regarding environmental hazard | ||
| 65 | mitigation and sustainable development. However, the process of | 65 | mitigation and sustainable development. However, the process of | ||
| 66 | classifying landforms is typically time-consuming and necessitates | 66 | classifying landforms is typically time-consuming and necessitates | ||
| 67 | specialized expertise. This research article presents a novel approach | 67 | specialized expertise. This research article presents a novel approach | ||
| 68 | that utilizes a convolutional neural network (CNN) to classify | 68 | that utilizes a convolutional neural network (CNN) to classify | ||
| 69 | valleys. The methodology involves employing an initial classification | 69 | valleys. The methodology involves employing an initial classification | ||
| 70 | generated by an unsupervised geomorphons classifier as input data, | 70 | generated by an unsupervised geomorphons classifier as input data, | ||
| 71 | which is subsequently refined using human-generated ground truth. In | 71 | which is subsequently refined using human-generated ground truth. In | ||
| 72 | contrast with the original geomorphons method, this novel method | 72 | contrast with the original geomorphons method, this novel method | ||
| 73 | enhances spatial coherence by effectively connecting pixels classified | 73 | enhances spatial coherence by effectively connecting pixels classified | ||
| 74 | as valleys. The results show that the proposed CNN-based method | 74 | as valleys. The results show that the proposed CNN-based method | ||
| 75 | significantly enhances the accuracy of the classification. We are | 75 | significantly enhances the accuracy of the classification. We are | ||
| 76 | confident our approach is competitive according to the Total Operating | 76 | confident our approach is competitive according to the Total Operating | ||
| 77 | Characteristic (TOC) curve as well as classification metrics.", | 77 | Characteristic (TOC) curve as well as classification metrics.", | ||
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