City University of Hong Kong

Versitech, Inc.

Antoni Bert Chan

Tei-Wei Kuo

Qi Zhang

Wuguannan Yao

Rynson Wing Hung Lau

Qiao Li

Yufei Cui

Xufang Pang

Chun Xue

Hui Wen Hsiao

Ying Cao

Ziquan Liu

Provided are an Eye Movement analysis with Hidden Markov Model (EMHMM) with co-clustering, an Eye Movement analysis with Switching Hidden Markov Models (EMSHMM) to analyze eye movement data in cognitive tasks involving stimuli with different feature layouts and cognitive state changes, a switching hidden Markov model (SHMM) to capture a participant's cognitive CN state transitions during the task and an EMSHMM to assess preference decision-making tasks with two or more cognitive states. The EMSHMM provides quantitative measures of individual differences in cognitive behavior/style, making a significant impact on the use of eye tracking to study cognitive behavior across disciplines.

Eye movement analysis with co-clustering of hidden Markov models (EMHMM with co-clustering) and with switching hidden Markov models (EMSHMM)

A computer-implemented method and a system for configuring and implementing an artificial neural network. The method for configuring includes initializing an artificial neural network; and training, based on a training operation, the artificial neural network so as to form an adaptively deployable artificial neural network defining a plurality of nested artificial neural sub-networks. Each artificial neural sub-network is optimal for a respective resource configuration. The method for implementing includes determining an optimal configuration of the artificial neural network for deployment at an electrical device, and deploying the artificial neural network with the optimal configuration at the electrical device.

Artificial neural network configuration and deployment

A method for optimizing a user interface comprising the steps of segmenting the user interface into one or more interface components each having one or more component characteristics; applying a user behaviour model to the one or more component characteristics of each of the one or more interface components to determine one or more user interaction paths of the one or more interface components; and processing the one or more user interaction paths to optimize the one or more interface components of the user interface.

System and method for optimizing a user interface and a system and method for manipulating a user's interaction with an interface

A system and a method for counting objects includes the steps of: obtaining a plurality of images representing the objects to be counted in a target area; generating a map for each of the plurality of images representing an identification of each of the corresponding objects; and fusing the plurality of maps being generated to obtain a scene-level density map representing a count of the objects in the target area.

System and method for counting objects

Growing community of inventors

Hong Kong, China

Antoni Bert Chan