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Found 4 papers, 1 papers with code
Uncovering the Metaverse within Everyday Environments: a Coarse-to-Fine Approach
The recent release of the Apple Vision Pro has reignited interest in the metaverse, showcasing the intensified efforts of technology giants in developing platforms and devices to facilitate its growth.
TransformCode: A Contrastive Learning Framework for Code Embedding via Subtree Transformation
Our framework has several advantages over existing methods: (1) It is flexible and adaptable, because it can easily be extended to other downstream tasks that require code representation (such as code-clone detection and classification); (2) it is efficient and scalable, because it does not require a large model or a large amount of training data, and it can support any programming language; (3) it is not limited to unsupervised learning, but can also be applied to some supervised learning tasks by incorporating task-specific labels or objectives; and (4) it can also adjust the number of encoder parameters based on computing resources.
Elongated Physiological Structure Segmentation via Spatial and Scale Uncertainty-aware Network
Second, we extract the uncertainty under different scales and propose the multi-scale uncertainty-aware (MSUA) fusion module to integrate structure contexts from hierarchical predictions, strengthening the final prediction.
Using Metamorphic Relations to Verify and Enhance Artcode Classification
An approach to software testing that alleviates the oracle problem is metamorphic testing (MT).
