Deep learning has achieved remarkable success in numerous domains with help from large amounts of big data. However, the quality of data labels is a concern because of the lack of high-quality labels ...

Researchers have long been interested in how humans and animals make decisions by focusing on trial-and-error behavior ...

Renesas Electronics Corporation (TSE:6723), a premier supplier of advanced semiconductor solutions, today introduced the ...

How reliable is artificial intelligence, really? An interdisciplinary research team at TU Wien has developed a method that ...

In the cerebral cortex, numerous neurons exchange information through junctions known as synapses. The strength of each ...

Despite achieving exceptional performance, deep neural networks (DNNs) suffer from the harassment caused by adversarial examples, which are produced by corrupting clean examples with tiny ...

Deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) are designed to partly emulate the functioning and structure of biological neural networks. As a ...

Neural Texture Compression (NTC) is a new technique that improves texture quality while reducing VRAM usage. It relies on a specialized neural network trained to compress ...

The brains of humans and other primates are known to execute various sophisticated functions, one of which is the representation of the space immediately surrounding the body. This area, also ...

StefanieJaeger / NeuralNet 3 Code Issues Pull requests machine-learning neural-network neural-networks machinelearning neural-network-example neuralnetwork neural-nets neuralnetworks Updated Sep 11, ...

We have been stuck in using neural network models to achieve radar target recognition for so many years. I just want to be back to the 90s and 00s, when people could also achieve complex tasks with a ...