In order to explore the possibilities of these complex spatio-temporal dynamics in image processing, a prototype chip has been developed by implementing this CNN model with analog signal processing ...

In Machine Translation (MT), one of most important research fields of AI, models based on Recurrent Neural Net- works (RNN) show state-of-the-art performance in recent years, and many researchers keep ...

Abstract: In this paper, we propose a new deep learning-based quality ranking framework to assist video list decoding methods in the context ... on a proven patch-based convolutional neural network ...

We conducted experiments using two distinct architectures. In first experiment we synergized ResNet-50 CNN with Support Vector Machine (SVM) algorithm and in the second model utilized the standard ...

Abstract: Neural machine translation (NMT) normally requires a large bilingual corpus to train a high-translation-quality model. However ... selection based on semantic similarity and decoder ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=6287639 ...

Recently, diffusion models have emerged as a new state-of-the-art deep learning method for image-to-image translation, better than traditional CNN-based methods. However, due to the high computation ...