neutrophils
发表于 2025-3-28 15:43:11
Traffic-Sign Recognition Using Deep Learning,r the traffic-sign recognition in New Zealand. In order to determine which deep learning models are the most suitable one for the TSR, we choose two kinds of models to conduct deep learning computations: Faster R-CNN and YOLOv5. According to the scores of various metrics, we summarized the pros and cons of the picked models for the TSR task.
Electrolysis
发表于 2025-3-28 18:45:28
Segment- and Arc-Based Vectorizations by Multi-scale/Irregular Tangential Covering,construct the input noisy objects into cyclic contours made of lines or arcs with a minimal number of primitives. We explain our novel complete pipeline in this work, and present its experimental evaluation by considering both synthetic and real image data.
Reclaim
发表于 2025-3-29 01:39:26
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Blatant
发表于 2025-3-29 06:40:49
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Iatrogenic
发表于 2025-3-29 07:41:40
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杂役
发表于 2025-3-29 13:29:50
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parsimony
发表于 2025-3-29 17:24:11
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小母马
发表于 2025-3-29 21:09:17
Apple Ripeness Identification Using Deep Learning,ifiers are able to achieve the best result, i.e., the ripeness class of an apple from a given digital image is able to be precisely predicted. We have optimized the deep learning models and trained the classifiers so as to achieve the best outcome.
collateral
发表于 2025-3-30 00:18:45
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pacifist
发表于 2025-3-30 04:13:44
Towards a Generic Bicubic Hermite Mesh Template for Cow Udders,ed correspondences occur due to data point occlusion and insufficient sampling points. In summary, a first parametric mesh based 3D model has been constructed for the cow udder and teat. We have examined the efficacy of the morphing algorithm, and also the issues to be solved for a statistical cow udder and teat model.