Multi-messenger astrophysics is a fast-growing, interdisciplinary field that combines data,
which vary in volume and speed of data processing, from many different instruments that …

Building a high-performance FPGA accelerator for Deep Neural Networks (DNNs) often
requires RTL programming, hardware verification, and precise resource allocation, all of …

Deep learning as performed by artificial deep neural networks (DNNs) has achieved great
successes recently in many important areas that deal with text, images, videos, graphs, and …

Increased variability of process parameters and recent progress in statistical static timing
analysis make extraction of statistical characteristics of process variation and spatial …

We consider the problem of unsupervised domain adaptation for semantic segmentation by
easing the domain shift between the source domain (synthetic data) and the target domain …

Recent region-based object detectors are usually built with separate classification and
localization branches on top of shared feature extraction networks. In this paper, we analyze …

When the training data are maliciously tampered, the predictions of the acquired deep
neural network (DNN) can be manipulated by an adversary known as the Trojan attack (or …

While embedded FPGAs are attractive platforms for DNN acceleration on edge-devices due
to their low latency and high energy efficiency, the scarcity of resources of edge-scale FPGA …

Abstract The Asiatic citrus psyllid Diaphorina citri Kuwayama (Hemiptera: Psyllidae) is a
major pest of citrus in China. Its status derives, not from the damage it causes, but from its …

This work provides a simple approach to discover tight object bounding boxes with only
image-level supervision, called Tight box mining with Surrounding Segmentation Context …