Arthur Jacobs, a professor and researcher at Freie Universität Berlin, has recently developed SentiArt, a new machine learning technique to carry out sentiment analyses of literary texts, as well as both fictional and non-fictional figures. In his paper, set to be...
Machine learning & AI
SPFCNN-Miner: A new classifier to tackle class-unbalanced data
Researchers at Chongqing University in China have recently developed a cost-sensitive meta-learning classifier that can be used when the training data available is high-dimensional or limited. Their classifier, called SPFCNN-Miner, was presented in a paper published...
Kaolin: The first comprehensive library for 3-D deep learning research
As most real-world environments are three-dimensional, deep learning models designed to analyze videos or complete tasks in real-world environments should ideally be trained on 3-D data. Technological tools such as robots, self-driving vehicles, smartphones, and other...
LeRop: A deep learning-based model to automatically capture human portraits
Taking good-quality photographs can be a challenging task, as it typically requires finding ideal locations, angles and lighting conditions. Although artistic pictures have so far primarily been taken by human photographers, in recent years, some researchers have...
New models for handwriting recognition in online Latin and Arabic scripts
Researchers at the University of Sfax, in Tunisia, have recently developed a new method to recognize handwritten characters and symbols in online scripts. Their technique, presented in a paper pre-published on arXiv, has already achieved remarkable performance on...
Infusing machine learning models with inductive biases to capture human behavior
Human decision-making is often difficult to predict and delineate theoretically. Nonetheless, in recent decades, several researchers have developed theoretical models aimed at explaining decision-making, as well as machine learning (ML) models that try to predict...
Distilled 3-D (D3D) networks for video action recognition
A team of researchers at Google, the University of Michigan and Princeton University have recently developed a new method for video action recognition. Video action recognition entails identifying particular actions performed in video footage, such as opening a door,...
EmoSense: an AI-powered and wireless emotion sensing system
Researchers at Hefei University of Technology in China and various universities in Japan have recently developed a unique emotion sensing system that can recognize people's emotions based on their body gestures. They presented this new AI- powered system, called...
Estimating people’s age using convolutional neural networks
Over the past few years, researchers have created a growing number of machine learning (ML)-based face recognition techniques, which could have numerous interesting applications, for instance, enhancing surveillance monitoring, security control, and potentially even...
ExAG: An image-guessing game to evaluate the helpfulness of machine explanations
In recent years, researchers have been trying to make artificial intelligence (AI) more transparent by developing algorithms that can explain their actions and behavior, as this could encourage greater trust in machines and enhance human-AI interactions. Despite their...