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Lifelong Text-Audio Sentiment Analysis learning.

Neural networks : the official journal of the International Neural Network Society
Sentiment analysis refers to the mining of textual context, which is conducted with the aim of identifying and extracting subjective opinions in textual materials. However, most existing methods neglect other important modalities, e.g., the audio mod...

Commonsense psychology in human infants and machines.

Cognition
Human infants are fascinated by other people. They bring to this fascination a constellation of rich and flexible expectations about the intentions motivating people's actions. Here we test 11-month-old infants and state-of-the-art learning-driven ne...

UDRN: Unified Dimensional Reduction Neural Network for feature selection and feature projection.

Neural networks : the official journal of the International Neural Network Society
Dimensional reduction (DR) maps high-dimensional data into a lower dimensions latent space with minimized defined optimization objectives. The two independent branches of DR are feature selection (FS) and feature projection (FP). FS focuses on select...

HCTNet: A hybrid CNN-transformer network for breast ultrasound image segmentation.

Computers in biology and medicine
Automatic breast ultrasound image segmentation helps radiologists to improve the accuracy of breast cancer diagnosis. In recent years, the convolutional neural networks (CNNs) have achieved great success in medical image analysis. However, it exhibit...

Resolving the associative learning paradox by category learning in pigeons.

Current biology : CB
A wealth of evidence indicates that humans can engage two types of mechanisms to solve category-learning tasks: declarative mechanisms, which involve forming and testing verbalizable decision rules, and associative mechanisms, which involve gradually...

The role of capacity constraints in Convolutional Neural Networks for learning random versus natural data.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are often described as promising models of human vision, yet they show many differences from human abilities. We focus on a superhuman capacity of top-performing CNNs, namely, their ability to learn very large dat...

Continual Object Detection: A review of definitions, strategies, and challenges.

Neural networks : the official journal of the International Neural Network Society
The field of Continual Learning investigates the ability to learn consecutive tasks without losing performance on those previously learned. The efforts of researchers have been mainly focused on incremental classification tasks. Yet, we believe that ...

Learning matrix factorization with scalable distance metric and regularizer.

Neural networks : the official journal of the International Neural Network Society
Matrix factorization has always been an encouraging field, which attempts to extract discriminative features from high-dimensional data. However, it suffers from negative generalization ability and high computational complexity when handling large-sc...

VISAL-A novel learning strategy to address class imbalance.

Neural networks : the official journal of the International Neural Network Society
In the imbalance data scenarios, Deep Neural Networks (DNNs) fail to generalize well on minority classes. In this letter, we propose a simple and effective learning function i.e, Visually Interpretable Space Adjustment Learning (VISAL) to handle the ...

A Study on the Role of Affective Feedback in Robot-Assisted Learning.

Sensors (Basel, Switzerland)
In recent years, there have been many approaches to using robots to teach computer programming. In intelligent tutoring systems and computer-aided learning, there is also some research to show that affective feedback to the student increases learning...