Minxiang YeUniversity of Strathclyde · Department of Electronic and Electrical Engineering (EEE)
Minxiang Ye
Doctor of Engineering
About
11
Publications
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130
Citations
Citations since 2017
Publications
Publications (11)
The image classification problem is to categorize elements of an image dataset into two or more pre‐defined classes based on inherent, detectable image features. Classification is typically posed in the context of supervised or semi‐supervised learning (SSL). This chapter discusses how SSL image classification can be mathematically formulated as op...
Convolutional neural network (CNN)-based feature learning has become the state-of-the-art for many applications since, given sufficient training data, CNN can significantly outperform traditional methods for various classification tasks. However, feature learning is more challenging if training labels are noisy as CNN tends to overfit to the noisy...
With the active large-scale roll-out of smart metering worldwide, details about the type of smart meter data that will be available for analysis are emerging. Consequently, focus has steadily been shifting from analysis of high-rate power readings (usually in kHz to MHz) to low-rate power readings (sampled at 1–60 s) and very low-rate meter reading...
Convolutional neural network (CNN)-based feature learning has become state of the art, since given sufficient training data, CNN can significantly outperform traditional methods for various classification tasks. However, feature learning becomes more difficult if some training labels are noisy. With traditional regularization techniques, CNN often...
Recent advances in image acquisition and analysis have resulted in disruptive innovation in physical rehabilitation systems facilitating cost-effective, portable, video-based gait assessment. While these inexpensive motion capture systems, suitable for home rehabilitation, do not generally provide accurate kinematics measurements on their own, imag...
With increasing importance given to telerehabilitation, there is a growing need for accurate, low-cost, and portable motion capture systems that do not require specialist assessment venues. This paper proposes a novel framework for motion capture using only a single depth camera, which is portable and cost effective compared to most industry-standa...
Gait analysis is often used as part of the rehabilitation program for post-stoke recovery assessment. Since current optical diagnostic and patient assessment tools tend to be expensive and not portable, this paper proposes a novel marker-based tracking system using a single depth camera which provides a cost-effective solution suitable for home and...
Driven by recent advances in information and communications technology, tele-rehabilitation services based on multimedia processing are emerging. Gait analysis is common for many rehabilitation programs, being, for example, periodically performed in the post-stroke recovery assessment. Since current optical diagnostic and patient assessment tools t...
Projects
Projects (2)
The goal of this project is to develop a novel integrated decision support mechanism embedding intelligent sensing, communications and data processing methodology for improving sustainability of smart buildings through new insights, approaches and technologies for acquisition, communications, and extraction of useful information from the sheer volume of sensed data in the built environment.
http://sensible.eee.strath.ac.uk/index.html
