As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...

An innovative partnership has yielded powerful new tools to help federal agencies rapidly synthesize complex data, historical ...

Diverse Domains Covered: Projects span NLP, vision, speech, and time-series. Tool-Centric Learning: Emphasis on libraries like TensorFlow, OpenCV, and Hugging Face. Practical and Scalable: Each task ...

A library of open datasets for data analytics/machine learning compiled by HackerNoon. The two most widely-used open-source machine learning frameworks for training and building deep learning models ...

Recent generations of machine learning, the methodology supporting artificial intelligence, have drawn inspiration from natural neural systems. These algorithmic approaches that mirror the complex ...

Abstract: Deep neural network (DNN) belongs to an important class of machine learning algorithms generally used to classify digital data in the form of image and speech recognition. The computational ...

This study proposes voltage-dependent-synaptic plasticity (VDSP), a novel brain-inspired unsupervised local learning rule for the online implementation of Hebb’s plasticity mechanism on neuromorphic ...

Abstract: Identification of the MNIST database that will be in handwritten digit can be recognized by the machine. It can be recognized that the human handwritten form into the machine language. Here ...

TensorFlow is an open-source framework developed by Google scientists and engineers for numerical computing. TensorFlow.NET is a library that provides a .NET Standard binding for TensorFlow, allowing ...

A spiking neural network model inspired by synaptic pruning is developed and trained to extract features of hand-written digits. The network is composed of three spiking neural layers and one output ...