Machine learning workloads require large datasets, while machine learning workflows require high data throughput. We can optimize the data pipeline to achieve both. Machine learning (ML) workloads ...

Abstract: Text to image transformation for input to neural networks requires intermediate steps. This paper attempts to present a new approach to pixel normalization so as to convert textual data into ...

Wang’s research involves taking incomplete data from scans of human patients (the input) and “reconstructing” a real image (the output). Image reconstruction is essentially the inverse of a more ...

We introduce the process of computing persistence homology and Betti sequences, which serve as vectorized input data for machine learning models. We propose two-channel deep learning models, with one ...

requiring less human input and boosting productivity. More personalized experiences: Machine learning algorithms will have the capacity to assess and make use of enormous volumes of data to ...

(Courtesy: Laura Gambini/TCD) A new machine-learning technique has significantly reduced noise in images taken by scanning transmission ... “Our algorithm doesn’t require any human input or prior ...