Over recent years, there has been a rapid development of deep learning (DL) in both
industry and academia fields. However, finding the optimal hyperparameters of a DL model …

Deep neural networks (DNNs) are currently being deployed as machine learning technology
in a wide range of important real-world applications. DNNs consist of a huge number of …

In the field of natural language processing (NLP), there have been various pre-training
language models in recent years, with question answering systems gaining significant …

From the control theory, bigger observer and controller gains are utilized to improve the
position perturbation attenuation, while smaller observer and controller gains are utilized to …

Over the past few years, larger and deeper neural network models, particularly convolutional
neural networks (CNNs), have consistently advanced state-of-the-art performance across …

Blueberry fruit in the picking process are characterized by small fruit particles, similar color
characteristics of immature fruits to leaf, and not obvious characteristics of fruits obscured by …

Evolutionary Computation algorithms have been used to solve optimization problems in
relation with architectural, hyper-parameter or training configuration, forging the field known …

Subsistence farmers and global food security depend on sufficient food production, which
aligns with the UN's “Zero Hunger,”“Climate Action,” and “Responsible Consumption and …

Despite the ongoing success of artificial intelligence applications, the deployment of deep
learning models on end devices remains challenging due to the limited onboard …

Structured pruning is a representative model compression technology for convolutional
neural networks (CNNs), aiming to prune some less important filters or channels of CNNs …