Deep multi-modal object detection and semantic segmentation for autonomous driving: Datasets, methods, and challenges
Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …
order to achieve robust and accurate scene understanding, autonomous vehicles are …
Deep multimodal learning: A survey on recent advances and trends
The success of deep learning has been a catalyst to solving increasingly complex machine-
learning problems, which often involve multiple data modalities. We review recent advances …
learning problems, which often involve multiple data modalities. We review recent advances …
Covid-19 outbreak prediction with machine learning
Several outbreak prediction models for COVID-19 are being used by officials around the
world to make informed decisions and enforce relevant control measures. Among the …
world to make informed decisions and enforce relevant control measures. Among the …
Adaptive probabilities of crossover and mutation in genetic algorithms
M Srinivas, LM Patnaik - IEEE Transactions on Systems, Man …, 1994 - ieeexplore.ieee.org
In this paper we describe an efficient approach for multimodal function optimization using
genetic algorithms (GAs). We recommend the use of adaptive probabilities of crossover and …
genetic algorithms (GAs). We recommend the use of adaptive probabilities of crossover and …
Evolving artificial neural networks
X Yao - Proceedings of the IEEE, 1999 - ieeexplore.ieee.org
Learning and evolution are two fundamental forms of adaptation. There has been a great
interest in combining learning and evolution with artificial neural networks (ANNs) in recent …
interest in combining learning and evolution with artificial neural networks (ANNs) in recent …
Optimizing connection weights in neural networks using the whale optimization algorithm
The learning process of artificial neural networks is considered as one of the most difficult
challenges in machine learning and has attracted many researchers recently. The main …
challenges in machine learning and has attracted many researchers recently. The main …
[BOOK][B] Estimation of distribution algorithms: A new tool for evolutionary computation
P Larrañaga, JA Lozano - 2001 - books.google.com
Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation is devoted to
a new paradigm for evolutionary computation, named estimation of distribution algorithms …
a new paradigm for evolutionary computation, named estimation of distribution algorithms …
The promise of implementing machine learning in earthquake engineering: A state-of-the-art review
Machine learning (ML) has evolved rapidly over recent years with the promise to
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
substantially alter and enhance the role of data science in a variety of disciplines. Compared …
Genetic algorithm-based clustering technique
A genetic algorithm-based clustering technique, called GA-clustering, is proposed in this
article. The searching capability of genetic algorithms is exploited in order to search for …
article. The searching capability of genetic algorithms is exploited in order to search for …
Metaheuristic design of feedforward neural networks: A review of two decades of research
Over the past two decades, the feedforward neural network (FNN) optimization has been a
key interest among the researchers and practitioners of multiple disciplines. The FNN …
key interest among the researchers and practitioners of multiple disciplines. The FNN …