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Found 10 papers, 1 papers with code
Dual-feature Fusion Attention Network for Small Object Segmentation
In this paper, we propose a dual feature fusion attention network (DFF-Net) to improve the segmentation accuracy of small objects.
Blockchain-enabled fraud discovery through abnormal smart contract detection on Ethereum
Therefore, this paper constructs a Heterogeneous Graph Transformer Networks (S_HGTNs) suitable for smart contract anomaly detection to detect financial fraud on the Ethereum platform.
Boundary-rendering network for breast lesion segmentation in ultrasound images
Breast Ultrasound (BUS) has proven to be an effective tool for the early detection of cancer in the breast.
An end-to-end neural network framework for SOH estimation and RUL prediction of lithium battery
Such prior distribution is regarded as a surrogate to investigate the degeneration data’s impact on modeling such NNs.
Local descriptor-based multi-prototype network for few-shot Learning
Prototype-based few-shot learning methods are promising in that they are simple yet effective to handle any-shot problems, and many prototype associated works are raised since then.
Unifying paragraph embeddings and neural collaborative filtering for hybrid recommendation
It adopts neural networks to exploit user–item ratings for collaborative filtering, which is endowed a high level of non-linearity for capturing the complex structure of user interaction ratings.
A stacking model using URL and HTML features for phishing webpage detection
In this paper, we present a stacking model to detect phishing webpages using URL and HTML features.
Multi-branch fusion network for hyperspectral image classification
Furthermore, the L2 regularization is introduced into this work to improve the generalization performance of the proposed model under small sample set.
SCFM: Social and crowdsourcing factorization machines for recommendation
Our approach fuses social and crowd computing into the factorization machine model.
Deriving land surface phenology indicators from CO2 eddy covariance measurements
Recent progress of CO2 eddy covariance (EC) technique and accumulation of measurements offer an unprecedented perspective to study the land surface phenology (LSP) in a more objective way than previously possible by allowing the actual photosynthesis measurement – gross primary productivity (GPP).
