Automated quantification of retinal vessel morphometry in the UK Biobank Cohort

The following topics are dealt with: feature extraction; learning (artificial intelligence); image classification; image segmentation; computer vision; object detection; feedforward neural nets; image colour analysis; image representation; medical image processing

Identifying Beetle Species Using Machine Learning

Machine learning Artificial Intelligence (AI) hold the potential to benefit farmers and the environment. Computer models can identify lady beetles in images, and, with more training, possibly determine their presence in crop fields. As predators, lady beetles could be a strong indicator of aphid infestations. Using this information and Al technology, farmers could simultaneously reduce costs and environmental damage by having the ability to identify an infested area and focus pesticide applications on a specified section rather than on an entire field,. Before we reach this point, we must determine whether Al or human identification is more reliable and efficient

Assessing the Quality of Swipe Interactions for Mobile Biometric Systems

The following topics are dealt with: face recognition; feature extraction; biometrics (access control); convolutional neural nets; learning (artificial intelligence); deep learning (artificial intelligence); iris recognition; image classification; image matching; image recognition

Parameterization of a Convolutional Autoencoder for Reconstruction of Small Images

The following topics are dealt with: mobile robots; control system synthesis; learning (artificial intelligence); feature extraction; robot vision; autonomous aerial vehicles; feedback; feedforward neural nets; nonlinear control systems; multi-robot systems

Preface

The following topics are dealt with: mobile robots; multi-robot systems; path planning; robot vision; service robots; collision avoidance; learning (artificial intelligence); legged locomotion; control engineering computing; production engineering computing.info:eu-repo/semantics/publishedVersio

Fostering Awareness and Personalization of Learning Artificial Intelligence

This paper illustrates the activities of the projects SMAILE and AILEAP, which are devoted to foster the growth of awareness and readyness to learn artificial intelligence in the general population. The first project was mainly oriented to children and young adults, while the second is more oriented to the personalization of the learning experience also in professionals