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SPM January 2021

Il N'y a ni Mauvaises Herbes ni Mauvais Hommes

A little over a century and a half ago, Victor Hugo wrote “Il n’y a ni mauvaises herbes ni mauvais hommes. Il n’y a que de mauvais cultivateurs,” which translates to “there are no weeds and no bad men. There are only bad cultivators.” These two sentences provide a stark reminder of the heavy responsibility we all bear, as parents, educators, mentors, members of professional societies, and citizens of states, nations, and earth. Indeed, arguably our main goal as a professional society is to help develop our human capital. Everything else flows from there.

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The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing

Enabling autonomous driving (AD) can be considered one of the biggest challenges in today?s technology. AD is a complex task accomplished by several functionalities, with environment perception being one of its core functions. Environment perception is usually performed by combining the semantic information captured by several sensors, i.e., lidar or camera. The semantic information from the respective sensor can be extracted by using convolutional neural networks (CNNs) for dense prediction. In the past, CNNs constantly showed stateof-the-art performance on several vision-related tasks, such as semantic segmentation of traffic scenes using nothing but the red-green-blue (RGB) images provided by a camera. 

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