Human observers can learn to recognize new categories of images from a handful of
examples, yet doing so with artificial ones remains an open challenge. We hypothesize that …

With the rapid development of machine learning, its powerful function in the machine vision
field is increasingly reflected. The combination of machine vision and robotics to achieve the …

Humans use multimodal sensory information to understand the physical properties of their
environment. Intelligent decision-making systems such as the ones used in robotic …

Storing and recalling spiking sequences is a general problem the brain needs to solve. It is,
however, unclear what type of biologically plausible learning rule is suited to learn a wide …

The standard scientific methodology in linguistics is empirical testing of falsifiable
hypotheses. As such the process of hypothesis generation is central, and involves …

With the rapid development of deep learning technology, many synthetic aperture radar
(SAR) target recognition algorithms based on convolutional neural networks have achieved …

Drug induced kidney injury is one of the leading causes of failure of drug development
programs in the clinic. Early prediction of renal toxicity potential of drugs is crucial to the …

Fault detection and diagnosis (FDD) is an important issue in building energy conservation.
This paper proposes a new option for solving this problem at the building level by using a …

The liquid and lyophilized blood plasma of patients with benign or malignant thyroid nodules
and healthy individuals were studied by terahertz (THz) time-domain spectroscopy and …

The energy consumption of a building has, in recent years, become a determining factor
during its design and construction. With carbon footprints being a growing issue, it is …