Глубокие нейронные сети в настоящее время становятся одним из самых популярных
подходов к созданию систем искусственного интеллекта, таких как распознавание …

Large-scale pre-trained models (PTMs) such as BERT and GPT have recently achieved
great success and become a milestone in the field of artificial intelligence (AI). Owing to …

Derin öğrenme makine öğreniminin bir koludur. Makine öğreniminin başlarından günümüze
kadar geçen süreçte yapay zekaya olan ilgi giderek artmış ve günümüzde en çok kullanılan …

Abstract Internet of Things (IoT) devices are increasingly deployed in different industries and
for different purposes (eg sensing/collecting of environmental data in both civilian and …

While deep learning methods have demonstrated performance comparable to human
readers in tasks such as computer-aided diagnosis, these models are difficult to interpret, do …

The internal representations of early deep artificial neural networks (ANNs) were found to be
remarkably similar to the internal neural representations measured experimentally in the …

One of the most important goals of seismic stratigraphy studies is to interpret the elements of
the seismic facies with respect to the geologic environment. Prestack seismic data carry rich …

Purpose To develop and evaluate a novel deep learning‐based image reconstruction
approach called MANTIS (Model‐Augmented Neural neTwork with Incoherent k‐space …

MRI is an advanced imaging modality with the unfortunate disadvantage of long data
acquisition time. To accelerate MR image acquisition while maintaining high image quality …

This paper introduces a new scalable multi-objective deep reinforcement learning (MODRL)
framework based on deep Q-networks. We develop a high-performance MODRL framework …