retrainable [ retrain ]的相关形容词;[ retraining ]的相关形容词 ai abbr. 1.=accidentally incurred 偶然招致的,遭遇意外 2.=artificial insemination人工授精 3.=artificial intellig AI (abbr. = artificial intelligence) 人工智能 人工智能,一般简称为AI,是研究、开发用于模拟、延伸和扩展人的智能的理论、方...
Why is '-ed' sometimes pronounced at the end of a word? Popular in Wordplay See All Top 12 Sophisticated Compliments Word of the Year 2024 | Polarization Terroir, Oenophile, & Magnum: Ten Words About Wine 8 Words for Lesser-Known Musical Instruments ...
Define retrainable. retrainable synonyms, retrainable pronunciation, retrainable translation, English dictionary definition of retrainable. tr. & intr.v. re·trained , re·train·ing , re·trains To train or undergo training again. re·train′a·ble adj.
Probabilistic Decision-Based Neural Networks (PDBNNs) can be considered as a special form of Gaussian Mixture Models (GMMs) with trainable decision thresho... KK Yiu,MW Mak,CK Li - 《Neural Computing & Applications》 被引量: 40发表: 1999年 Dissimilarities for Web Usage Mining Studies in Class...
David Rine, Software perfective maintenance: including retrainable software in software reuse, Information Sciences: an International Journal, v.75 n.1-2, p.109-132, Dec. 1, 1993 [doi>10.1016/0020-0255(93)90116-4]Rine, D. "Software perfective maintenance - including retrainable software in ...
This pull request adds major functionality and documentation for re-training Parametric UMAP models, and using landmark re-training to keep the embedding space consistent. This feature allows for t...
Unsupervised Stereoscopic Video Object Segmentation Based on Active Contours and Retrainable Neural Networks 来自 ResearchGate 喜欢 0 阅读量: 45 作者:K Ntalianis,A Doulamis,N Doulamis 摘要: In this paper an unsupervised scheme for stereoscopic video object extraction is presented based on a neural ...
This section will introduce the structure and the training process of the retrainable Siamese network. 3.1. Introduction of the Siamese Network The new load cannot be predicted, as it could appear at any time. The modern NILM system should be able to identify these new loads [28] and improve...
We demonstrate that architectures which traditionally are considered to be ill-suited for a task can be trained using inductive biases from another architecture. Networks are considered untrainable when they overfit, underfit, or converge to poor results even when tuning their hyperparameters. For exa...