AIMC Topic: Learning

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Implementation of Learning Management Systems (LMS) in higher education systems through bipolar complex hesitant fuzzy Aczel-Alsina power aggregation operators: A case review for China.

PloS one
A learning management system (LMS) is a web-based application or software platform computed to facilitate the development, tracking, management, reporting, and delivery of education and training programs. Many valuable and dominant factors are workin...

Bi-DexHands: Towards Human-Level Bimanual Dexterous Manipulation.

IEEE transactions on pattern analysis and machine intelligence
Achieving human-level dexterity in robotics remains a critical open problem. Even simple dexterous manipulation tasks pose significant difficulties due to the high number of degrees of freedom and the need for cooperation among heterogeneous agents (...

Audiovisual Moments in Time: A large-scale annotated dataset of audiovisual actions.

PloS one
We present Audiovisual Moments in Time (AVMIT), a large-scale dataset of audiovisual action events. In an extensive annotation task 11 participants labelled a subset of 3-second audiovisual videos from the Moments in Time dataset (MIT). For each tria...

Data-driven normative values based on generative manifold learning for quantitative MRI.

Scientific reports
In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region of an individual versus a control group are often provided as deviations from so-called normal values. These normative reference values are traditiona...

Teaching robots the art of human social synchrony.

Science robotics
Humanoid robots can now learn the art of social synchrony using neural networks.

Human-robot facial coexpression.

Science robotics
Large language models are enabling rapid progress in robotic verbal communication, but nonverbal communication is not keeping pace. Physical humanoid robots struggle to express and communicate using facial movement, relying primarily on voice. The ch...

Robust Deep Neural Network for Learning in Noisy Multi-Label Food Images.

Sensors (Basel, Switzerland)
Deep networks can facilitate the monitoring of a balanced diet to help prevent various health problems related to eating disorders. Large, diverse, and clean data are essential for learning these types of algorithms. Although data can be collected au...

A number sense as an emergent property of the manipulating brain.

Scientific reports
The ability to understand and manipulate numbers and quantities emerges during childhood, but the mechanism through which humans acquire and develop this ability is still poorly understood. We explore this question through a model, assuming that the ...

Can neural networks benefit from objectives that encourage iterative convergent computations? A case study of ResNets and object classification.

PloS one
Recent work has suggested that feedforward residual neural networks (ResNets) approximate iterative recurrent computations. Iterative computations are useful in many domains, so they might provide good solutions for neural networks to learn. However,...