Enhancing Cyber Security of LoRaWAN Gateways under Adversarial Attacks.

The Internet of Things (IoT) has disrupted the IT landscape drastically, and Long Range Wide Area Network (LoRaWAN) is one specification that enables these IoT devices to have access to the Internet. Former security analyses have suggested that the gateways in LoRaWAN in their current state are susceptible to a wide variety of malicious attacks, which can be notoriously difficult to mitigate since gateways are seen as obedient relays by design. These attacks, if not addressed, can cause malfunctions and loss of efficiency in the network traffic.

Emotion Recognition on Edge Devices: Training and Deployment.

Emotion recognition, among other natural language processing tasks, has greatly benefited from the use of large transformer models. Deploying these models on resource-constrained devices, however, is a major challenge due to their computational cost. In this paper, we show that the combination of large transformers, as high-quality feature extractors, and simple hardware-friendly classifiers based on linear separators can achieve competitive performance while allowing real-time inference and fast training.

T-RexNet-A Hardware-Aware Neural Network for Real-Time Detection of Small Moving Objects.

This paper presents the T-RexNet approach to detect small moving objects in videos by using a deep neural network. T-RexNet combines the advantages of Single-Shot-Detectors with a specific feature-extraction network, thus overcoming the known shortcomings of Single-Shot-Detectors in detecting small objects. The deep convolutional neural network includes two parallel paths: the first path processes both the original picture, in gray-scale format, and differences between consecutive frames; in the second path, differences between a set of three consecutive frames is only handled.

Active Haptic Perception in Robots: A Review.

In the past few years a new scenario for robot-based applications has emerged. Service and mobile robots have opened new market niches. Also, new frameworks for shop-floor robot applications have been developed.

Real-Time Digital Signal Processing Based on FPGAs for Electronic Skin Implementation.

Enabling touch-sensing capability would help appliances understand interaction behaviors with their surroundings. Many recent studies are focusing on the development of electronic skin because of its necessity in various application domains, namely autonomous artificial intelligence (e.g.