New Machine
Research on "new machines" broadly encompasses the development and application of machine learning across diverse fields, aiming to improve efficiency, accuracy, and decision-making. Current efforts focus on refining model architectures like convolutional neural networks, gradient boosting machines, and transformers for tasks ranging from image and signal processing to complex prediction and control problems. This research is significant because it drives advancements in various sectors, including healthcare, energy, manufacturing, and transportation, by enabling automated processes, improved diagnostics, and more efficient resource allocation.
Papers
Machine learning in the prediction of cardiac epicardial and mediastinal fat volumes
É. O. Rodrigues, V. H. A. Pinheiro, P. Liatsis, A. Conci
A Dataset and Baseline Approach for Identifying Usage States from Non-Intrusive Power Sensing With MiDAS IoT-based Sensors
Bharath Muppasani, Cheyyur Jaya Anand, Chinmayi Appajigowda, Biplav Srivastava, Lokesh Johri