Blockchain-Based Traceability for the Fishery Supply Chain

Abstract: Conventional deformable registration methods solve an image pair optimization model, which is computationally expensive. Recent deep learning-based methods estimate deformation quickly. These data-driven heuristic network architectures lack geometric constraints needed to generate plausible topology-preserving…

Abstract: Social network analyses and applications face the user alignment problem, which matches users across networks. State-of-the-art methods embed users into the low-dimensional representation space, where their features are preserved, and establish user correspondence based…

Abstract: Unbalanced data can strongly bias classifiers toward the majority class. GAN methods have been proposed to address this issue. Existing GAN-based methods fail to exploit the classifier-generator relationship. This article proposes a novel three-player…

Abstract: Most nations want to cut greenhouse gas emissions. Some governments have tried hard to fix this. Saudi Arabia has invested heavily in renewable energy (RE) sources. Consumers should build small RE systems. Small grids…

Abstract: Hypergraph learning teaches hypergraph structures. Due to its flexibility and ability to model complex data correlation, hypergraph learning has gained popularity. First, we review distance-based, representation-based, attribute-based, and network-based hypergraph generation literature. Transductive, inductive,…

Abstract: Background clutter often affects RGBT tracking methods that localize a target object with a bounding box. This article introduces noise-robust cross-modal ranking to reduce background effects in RGBT target bounding boxes. We address noise…