ABSTRACT: Convolutional neural networks (CNNs) are widely used in image classification tasks, but their increasing model size and computation make them challenging to implement on embedded systems ...

AI training and inference are all about running data through models — typically to make some kind of decision. But the paths that the calculations take aren’t always straightforward, and as a model ...

Spring Batch provides developers with two separate approaches to batch programming: 1. Process a small batch of records in a single step using a Tasklet. 2. Process a large batch of records in chunks ...

Even though batch files are like vintage when it comes to operating systems, they are one of the best ways to get things done. If you are in a kind of work that asks you to run some pre-defined ...

Abstract: We present Sandwich Batch Normalization (SaBN), a frustratingly easy improvement of Batch Normalization (BN) with only a few lines of code changes. SaBN is motivated by addressing the ...

Abstract: A well-known issue of Batch Normalization is its significantly reduced effectiveness in the case of small mini-batch sizes. When a mini-batch contains few examples, the statistics upon which ...

Spiking Neural Networks (SNNs) have recently emerged as an alternative to deep learning owing to sparse, asynchronous and binary event (or spike) driven processing, that can yield huge energy ...

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