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Cylindrical Lithium-Ion Batteries have been widely used as power source for electric and hybrid vehicles because of their compact size and high power density. The battery pack is commonly consisted by hundreds of cylindrical Lithium-Ion battery cells in several strings. Because the distance among battery cells is only a few millimeters, the thermal status of battery would directly influent the current...
Among learning based hashing methods, supervised hashing seeks compact binary representation of the training data to preserve semantic similarities. Recent years have witnessed various problem formulations and optimization methods for supervised hashing. Most of them optimize a form of loss function with a regulization term, which can be viewed as a maximum a posterior (MAP) estimation of the hashing...
Hashing for similarity search in large scale data has become an increasingly popular technique. K-means Hashing (KMH) has been proven effective because of the benefits of adaptive k-means quantization. However, KMH is a batch-based learning model requiring high time and storage complexities, which makes it hard to load large scale data into memory to train and deal with streaming data. To address...
Spectral clustering is one of the most popular clustering approaches with the capability to handle some challenging clustering problems. Only a little work of spectral clustering focuses on the explicit linear map which can be viewed as the distance metric learning. In practice, the selection of the affinity matrix exhibits a tremendous impact on the unsupervised learning. In this paper, we propose...
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