Image recognition is an important task in computer vision with broad applications. In recent
years, with the advent of deep learning, lightweight convolutional neural network (CNN) has …

Determining the architecture of deep learning models is a complex task. Several automated
search techniques have been proposed, but these methods typically require high …

Home service robots face a challenge in accurately and promptly detecting small objects in
unstructured scenarios when the target is far from the robot vision system. Therefore, a …

Methaheuristics (MHs) are techniques widely used for solving complex optimization
problems. In recent years, the interest in combining MH and machine learning (ML) has …

The deployment of Deep Neural Networks (DNNs) requires significant computational and
storage resources, which is challenging for resource-constrained end devices. To this end …

Accurate classification of medical images is essential for modern diagnostics. Deep learning
advancements led clinicians to increasingly use sophisticated models to make faster and …

Neural architecture search (NAS) has proven to be effective at automating the design of
neural network architectures and hyperparameters. The design produced by NAS is …

The following article presents the development of an algorithm embedded in a Raspberry Pi
3B board, where a user identification was made, using the convolutional neural network …

The deployment of neural networks on resource-constrained hardware requires architecture
optimization algorithms that respect accuracy and computational cost. One emerging way for …

This paper proposes an innovative approach for generating the topology of artificial neural
networks. The proposed method utilizes an iterative function system (IFS) to produce …