Grain production plays an important role in the global economy. In this sense, the demand
for efficient and safe methods of food production is increasing. Information Technology is …

In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …

Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

Several variants of the long short-term memory (LSTM) architecture for recurrent neural
networks have been proposed since its inception in 1995. In recent years, these networks …

Reduced Order Modeling (ROM) for engineering applications has been a major research
focus in the past few decades due to the unprecedented physical insight into turbulence …

We propose RUDDER, a novel reinforcement learning approach for delayed rewards in
finite Markov decision processes (MDPs). In MDPs the Q-values are equal to the expected …

Acoustic novelty detection aims at identifying abnormal/novel acoustic signals which differ
from the reference/normal data that the system was trained with. In this paper we present a …

Highlights•Defects affecting horticultural products and detection challenges are
summarised.•Machine learning's role in addressing issues of fruit defect detection is …

Recently accrued attention has been given to machine learning approaches for flooding
prediction. However, most of these studies focused mainly on time-series flooding prediction …

While neural networks have acted as a strong unifying force in the design of modern AI
systems, the neural network architectures themselves remain highly heterogeneous due to …