Artificial neural networks (ANNs) are massively parallel systems with large numbers of interconnected simple processors. This paper describes a computational model to support decision-making using a combination of data mining (DM) and artificial neural network (ANN). With the enormous amount of data ...
‘black box’ models derived from ANN can be really difficult to analyse using 2D or 3D plots (Figure 2.4). One can stand in front of a wonderful non-linear model and an excellent collection of graphs showing the effects of inputs on outputs and still maintain the great question: ‘And,...
The goal was always to sequentially train the neural network on all tasks or episodes of the task protocol, whereby the network only had access to the data of the current task/episode. For all methods considered in this paper, during training the parameters θ of the neural network were upda...
Researchers at FORTH have developed a new type of artificial neural network (ANN) that incorporates features of biological dendrites. This innovative design allows for accurate and robust image recognition while using significantly ... Feb 5, 2025 0 47 Security Constitutional classifiers: New secu...
Artificial Neural Network Architectures (ANN) Initially introduced by McCulloch and Pitts (1943) and in the form of a simple perceptron by Rosenblatt (1958), ANNs have gained major traction in the AI community. ANNs are highly applicable in the domain of statistical machine learning in which the...
Following the conventions of Keras, a question mark refers to an existing dimension of unknown size which here denotes the batch size and Lambda layers refer to user defined functions inside the network architecture. Here, the input is given by the deformation gradient F. The precise number of ...
Brain MR image classification for glioma tumor detection using deep convolutional neural network features. Curr. Med. imaging 17, 56–63 (2021). CAS PubMed Google Scholar Saeedi, S., Rezayi, S., Keshavarz, H. & R. Niakan Kalhori, S. MRI-based brain tumor detection using convolutional...
Maximal Overlap Discrete Wavelet Transform (MODWT); Artificial Neural Network (ANN). The possibilities for combining methods are vast for the supply chain. At this point, one of the most important points is to have a good overview of the AI and simulation that can be used to realize the ...
Alan Turing publishesComputing Machinery and Intelligence. In this paper, Turing—famous for breaking the German ENIGMA code during WWII and often referred to as the "father of computer science"—asks the following question: "Can machines think?" ...
To address this question, we used such benchmarks to evaluate the visual and auditory models described above in Figs.2–5. For the visual models, we used the Brain-Score platform to measure the similarity of model representations to neural benchmarks for visual areas V1, V2 and V4 and th...