Haku

Multiradar tracking of aircraft is a sensor fusion problem including complicated measurement and object motion models. The accuracy of radar measurements differs significantly between bearing and range. The transformation ...

In recent years, natural language processing has advanced by creating new ways of modeling text using deep neural networks. These new models have demonstrated state of-the-art performance in several natural language ...

The cryptocurrency market is considered high-risk compared to traditional investment channels such as stocks or bonds. The whole market trend is primarily affected by only a few top-of-the-market capitalization cryptocurrencies ...

Machine vision tasks such as object detection and instance segmentation are becoming more and more popular these days due to the quickly increasing performance of deep neural networks. Consequently, more and more multimedia ...

With an increased popularity of Machine Learning (ML) and Deep Learning (DL) companies have started to offer Machine Learning as a Service (MLaaS). These services are under threat due to vulnerabilities in privacy that ...

Detecting and localizing tree trunks is a necessary component for automatic harvesting machines. This task can be split into two sub-tasks: object detection and depth estimation. Object detection is a crucial problem that ...

Teaching neural network models to classify new tasks and old tasks on new domains is a process, where a common problem is the forgetting of previous tasks and/or domains. This problem is referred to as catastrophic forgetting. ...

Recent research of deep learning approaches has resulted in many novel and high-performing models being developed. Simultaneously, the interest in hardware acceleration of neural networks has been constantly growing. This ...

With the global demand for industrial and home automation growing, new solutions that utilize existing installations are needed. Neural network-based solutions have been introduced to the field, but they lack configurability. ...