Many current state-of-the-art outdoor robots have perception systems that are primarily hand-tuned, which makes them difficult to adapt to new tasks and environments. Machine learning offers a practical solution to this problem. Assuming that training data describing the desired output of the system is available, many supervised learning algorithms exist for automatically adjusting the paramete...

PURPOSE This study aimed to compare the perception of the academic learning environment between medical laboratory science students and nursing students at Saint Louis University, Baguio City, Philippines. METHODS A cross-sectional survey research design was used to measure the perceptions of the participants. A total of 341 students from the Department of Medical Laboratory Science, School o...

The quality of education depends on the quality of technology. Information and communication technology (ICT) has become popular within a very short time one of the basic building blocks of modern society. The present study was aim to find out the perception of teacher trainees towards learning through information and communication technologies. The objectives of the study were to find out the ...

Deep-layer machine learning architectures continue to emerge as a promising biologically-inspired framework for achieving scalable perception in artificial agents. State inference is a consequence of robust perception, allowing the agent to interpret the environment with which it interacts and map such interpretation to desirable actions. However, in existing deep learning schemes, the percepti...

The proposed Perception Evolution Network (PEN) is a biologically inspired neural network model for unsupervised learning and online incremental learning. It is able to automatically learn suitable prototypes from learning data in an online incremental way, and it does not require the predefined prototype number and similarity threshold. Meanwhile, being more advanced than the existing unsuperv...

The present study, pertaining to a national information literacy training program for both farmers and rural communities in Taiwan, explores factors that affect learners’ perception of learning information and communication technology (ICT). It further analyzes effects of individual characteristics and varied training designs on learners’ perception of learning ICT. Data used for analyses deriv...

Visual perception is strongly shaped by expectations, but it is poorly understood how such perceptual expectations are learned in our dynamic sensory environment. Here, we applied a Bayesian framework to investigate whether perceptual expectations are continuously updated from different aspects of ongoing experience. In two experiments, human observers performed an associative learning task in ...

Research in music cognition domain has shown that non musician listeners have implicit knowledge about the Western tonal musical system. This knowledge, acquired by mere exposure to music in everyday life, influences perception of musical structures and allows developing expectations for future incoming events. Musical expectations play a role for musical expressivity and influence event proces...

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is con...