BOHR International Journal of Internet of things, Artificial Intelligence and Machine Learning (BIJIAM) is an open access peer-reviewed journal that publishes articles which contribute new results in all the areas of Internet of things, Artificial Intelligence and Machine Learning. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in this area.
Published: 2023-01-03
Methods
Emotion Recognition Based on Speech Signals by Combining Empirical Mode Decomposition and Deep Neural Network
Article Type : Methods
DOI: 10.54646/bijiam.2023.111-10
Discrete clusters formulation through the exploitation of optimized k-modes algorithm for hypotheses validation in social work research: the case of greek social workers working with refugees
Article Type : Methods
DOI: 10.54646/bijiam.2023.1211-18
Drug recommendation using recurrent neural networks augmented with cellular automata
Article Type : Methods
DOI: 10.54646/bijiam.2023.1319-25
Research
Prognostication of the placement of students applying machine learning algorithms
Article Type : Research
DOI: 10.54646/bijiam.2023.1426-30
Object detection and ship classification using YOLO and Amazon Rekognition
Article Type : Research
DOI: 10.54646/bijiam.2023.1647-57
Prevention of fire and hunting in forests using machine learning for sustainable forest management
Article Type : Research
DOI: 10.54646/bijiam.2023.1758-64
Air quality forecasting using convolutional neural networks
Article Type : Research
DOI: 10.54646/bijiam.2023.1865-69
Concept Development
Machine learning for autonomous online exam fraud detection: A concept design
Article Type : Concept Development
DOI: 10.54646/bijiam.2023.1531-36