Nature communications
Jun 14, 2022
There is a growing trend to design hybrid neural networks (HNNs) by combining spiking neural networks and artificial neural networks to leverage the strengths of both. Here, we propose a framework for general design and computation of HNNs by introdu...
Computational intelligence and neuroscience
Jun 11, 2022
Instructional practices have undergone a drastic change as a result of the development of new educational technology. Artificial intelligence (AI) as a teaching and learning technology will be examined in this theoretical review study. To enhance the...
Sensors (Basel, Switzerland)
Jun 10, 2022
In this study, we propose a method for inspecting the condition of hull surfaces using underwater images acquired from the camera of a remotely controlled underwater vehicle (ROUV). To this end, a soft voting ensemble classifier comprising six well-k...
Nature communications
Jun 7, 2022
Deep generative models of molecules have grown immensely in popularity, trained on relevant datasets, these models are used to search through chemical space. The downstream utility of generative models for the inverse design of novel functional compo...
Computational and mathematical methods in medicine
Jun 7, 2022
Preschool language education is a requirement of basic education reform as well as a requirement for children's growth in all aspects of body and mind. It is extremely important and valuable in encouraging the entire growth of preschool education as ...
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jun 5, 2022
Realization of memristor-based neuromorphic hardware system is important to achieve energy efficient bigdata processing and artificial intelligence in integrated device system-level. In this sense, uniform and reliable titanium oxide (TiO ) memristor...
Neural networks : the official journal of the International Neural Network Society
Jun 4, 2022
Graph Neural Networks (GNNs) have been widely applied to various fields due to their powerful representations of graph-structured data. Despite the success of GNNs, most existing GNNs are designed to learn node representations on the fixed and homoge...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
Domain Adaptation aims at adapting the knowledge learned from a domain (source-domain) to another (target-domain). Existing approaches typically require a portion of task-relevant target-domain data a priori. We propose an approach, zero-shot deep do...
IEEE transactions on pattern analysis and machine intelligence
Jun 3, 2022
Despite the remarkable progress achieved in conventional instance segmentation, the problem of predicting instance segmentation results for unobserved future frames remains challenging due to the unobservability of future data. Existing methods mainl...
Sensors (Basel, Switzerland)
Jun 2, 2022
Unsupervised domain adaptation, which aims to alleviate the domain shift between source domain and target domain, has attracted extensive research interest; however, this is unlikely in practical application scenarios, which may be due to privacy iss...