DASIP

The use of neural networks represents the state of the art in the area of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically,...

Testing and evaluation of an automotive perception system is a complicated task which requires special equipment and infrastructure. To compute key performance indicators and compare the results with the real-world situation, some additional sensors ...

Capsule Networks (CapsNets) are the new generation of classifiers with several advantages over the previous ones. Such advantages include higher robustness to affine transformed datasets and detection of overlapping images. CapsNets, while obtaining ...

The Dynamic Execution Integrity Engine (DExIE) is a lightweight hardware monitor that can be flexibly attached to many IoT-class processor pipelines. It is guaranteed to catch both inter- and intra-function illegal control flows in time to prevent any ...

Tangled Program Graph (TPG) is a reinforcement learning technique based on genetic programming concepts. On state-of-the-art learning environments, TPGs have been shown to offer comparable competence with Deep Neural Networks (DNNs), for a fraction of ...

In this paper, we present a hardware-software implementation of a deep neural network for object detection based on a point cloud obtained by a LiDAR sensor. The Brevitas / PyTorch tools were used for network quantisation and the FINN tool for hardware ...

Fully integrated CMOS frequency-modulated continuous-wave radar ICs are under development, in which computing FFTs cost a significant amount of energy.

In this paper we introduce a power-efficient FFT solution which exploits that intermediate results ...

Recent studies predict that video data accounts for 82% of Internet traffic by 2022. This fact has motivated MPEG to define a new Video Coding Standard called Versatile Video Coding (VVC), which will be released by the end of 2020. VVC will offer the ...

The dataflow paradigm frees the designer to focus on the functionality of an application, independently from the underlying architecture executing it. While mapping the dataflow computational part to the cores seems obvious, the memory aspects do not ...