This paper presents a reinforcement learning approach for foreign exchange trading. Inspired by technical analysis methods, this approach makes use of technical indicators by encoding them into Gramian Angular Fields and searches for patterns that indicate price movements using convolutional… Read More »Scalp the Foreign Exchange Market with Deep Reinforcement Learning
In the last few decades, text mining has been used to extract knowledge from free texts. Applying neural networks and deep learning to natural language processing (NLP) tasks has led to many accomplishments for real-world language problems over the years.… Read More »Language Representation Models: An Overview
Deep learning methods have gained attention in predictive process mining tasks. The most popular architectures include Recurrent Neural Networks and Convolutional Neural Networks. Inspired by the fact that Graph Neural Networks can operate directly on graph data, this work proposes… Read More »Predictive Business Process Monitoring using Graph Neural Networks
This work introduces Multi-Fusion Network for human-object interaction detection with multiple cameras. We present a concept and implementation of the architecture for a beverage refrigerator with multiple cameras as proof-of-concept. We also introduce an effective approach for minimizing the required… Read More »Recognizing Human-Object Interaction in Multi-Camera Environments