Performance Metrics of the Model: The effectiveness of AI-based hardware Trojan (HT) detection models can be assessed by a range of classification metrics, including accuracy, precision, recall (true ...

In order to reduce the impact of imbalance samples on load identification, the SVM SMOTE algorithm is used to balance the samples. Based on the deep learning method, the convolutional neural network ...

Techniques such as recurrent neural networks, graph theory ... attention, memory, decision-making, learning, and language. Relevant themes include neural coding, network dynamics, brain-inspired ...

In a network, pairs of individual elements, or nodes, connect to each other; those connections can represent a sprawling system with myriad individual links. A hypergraph goes deeper: It gives ...

the Hong Kong Orchid Tree Bauhinia x blakeana Dunn. A new software algorithm developed at Caltech enables researchers to easily search for viruses in RNA sequence data, enabling scientists to ...

Attention Heads,Binary Phase Shift Keying,Classification Accuracy,Convolutional Neural Network,Cross-correlation,Feature Matrix,Global Features,Global Relations,Graph Attention,Graph Attention Network ...

Here a machine learning algorithm will be trained to predict a liver disease in patients using a data-set collected from North East of Andhra Pradesh, India. Using machine learning models to predict ...

A benchmarking toolkit for comparing Kruskal's and Prim's minimum spanning tree algorithms across various graph configurations, with visualization tools and performance analysis reports. A collection ...