T.M. Mcginnity

T.M. Mcginnity
Nottingham Trent University | NTU · School of Science and Technology

BSc Physics, PhD

About

384
Publications
71,210
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6,032
Citations

Publications

Publications (384)
Preprint
Robots are expected to grasp a wide range of objects varying in shape, weight or material type. Providing robots with tactile capabilities similar to humans is thus essential for applications involving human-to-robot or robot-to-robot interactions, particularly in those situations where a robot is expected to grasp and manipulate complex objects no...
Article
Vertebrate retinas are highly-efficient in processing trivial visual tasks such as detecting moving objects, yet a complex challenges for modern computers. In vertebrates, the detection of object motion is performed by specialised retinal cells named Object Motion Sensitive Ganglion Cells (OMS-GC). OMS-GC process continuous visual signals and gener...
Conference Paper
The retina acts as the primary stage for the encoding of visual stimuli in the central nervous system. It is comprised of numerous functionally distinct cells tuned to particular types of visual stimuli. This work presents an analytical approach to identifying contrast-driven retinal cells. Machine learning approaches as well as traditional regress...
Preprint
Full-text available
The detection of moving objects is a trivial task performed by vertebrate retinas, yet a complex computer vision task. Object-motion-sensitive ganglion cells (OMS-GC) are specialised cells in the retina that sense moving objects. OMS-GC take as input continuous signals and produce spike patterns as output, that are transmitted to the Visual Cortex...
Preprint
Full-text available
Robots need to exploit high-quality information on grasped objects to interact with the physical environment. Haptic data can therefore be used for supplementing the visual modality. This paper investigates the use of Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) neural network architectures for object classification on Spat...
Article
Full-text available
The detection of moving objects is a trivial task performed by vertebrate retinas, yet a complex computer vision task. Object-motion-sensitive ganglion cells (OMS-GC) are specialised cells in the retina that sense moving objects. OMS-GC take as input continuous signals and produce spike patterns as output, that are transmitted to the Visual Cortex...
Chapter
The retina acts as the primary stage for the encoding of visual stimuli in the central nervous system. It is comprised of numerous functionally distinct cells tuned to particular types of visual stimuli. This work presents an analytical approach to identifying contrast-driven retinal cells. Machine learning approaches as well as traditional regress...
Chapter
At the time of writing, the Covid-19 pandemic is continuing to spread across the globe with more than 135 million confirmed cases and 2.9 million deaths across nearly 200 countries. The impact on global economies has been significant. For example, the Office for National Statistics reported that the UK’s unemployment level increased to 5% and the h...
Conference Paper
Full-text available
Robots need to exploit high-quality information on grasped objects to interact with the physical environment. Haptic data can therefore be used for supplementing the visual modality. This paper investigates the use of Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) neural network architectures for object classification on Spat...
Article
Full-text available
A growing body of evidence supports an important role for alterations in the brain-gut-microbiome axis in the aetiology of depression and other psychiatric disorders. The potential role of the oral microbiome in mental health has received little attention, even though it is one of the most diverse microbiomes in the body and oral dysbiosis has been...
Conference Paper
Full-text available
Time series data from multiple modalities such as physiological and motion sensor data have proven to be integral for measuring mental wellbeing however individual differences between people limit the generalisability of deep learning models especially for those with intellectual disabilities. It is impractical, time consuming and extremely challen...
Preprint
Full-text available
Microbiota profiles measure the structure of microbial communities in a defined environment (known as microbiomes). In the past decade, microbiome research has focused on health applications as a result of which the gut microbiome has been implicated in the development of a broad range of diseases such as obesity, inflammatory bowel disease, and ma...
Article
The ability to quickly and accurately triage a person’s medical condition in an emergency situation or other critical scenarios could mean the difference between life and death. Endowing a robotic system with vision and tactile capabilities, similar to those of medical professionals, and thus enabling robots to assess a patient’s status in an emerg...
Preprint
Full-text available
Involving and engaging people with learning disabilities on issues relating to their mental wellbeing can bechallenging. This research explores how participatory design techniques and principles can be used to engagepeople with learning disabilities in designing technological solutions relevant to them that could monitorand aid their mental wellbei...
Article
Full-text available
Recent technological advancements in data acquisition tools allowed life scientists to acquire multimodal data from different biological application domains. Categorized in three broad types (i.e. images, signals, and sequences), these data are huge in amount and complex in nature. Mining such enormous amount of data for pattern recognition is a bi...
Conference Paper
Full-text available
Over the last few years, the number of precision farming projects has increased specifically in harvesting robots and many of which have made continued progress from identifying crops to grasping the desired fruit or vegetable. One of the most common issues found in precision farming projects is that successful application is heavily dependent not...
Preprint
Over the last few years, the number of precision farming projects has increased specifically in harvesting robots and many of which have made continued progress from identifying crops to grasping the desired fruit or vegetable. One of the most common issues found in precision farming projects is that successful application is heavily dependent not...
Conference Paper
Model optimisation is a key step in model development and traditionally this was limited to parameter tuning. However, recent developments and enhanced understanding of internal dynamics of model architectures have led to various exploration to optimise and enhance performance through model extension and development. In this paper, we extend the ar...
Article
Ensemble models achieve high accuracy by combining a number of base estimators and can increase the reliability of machine learning compared to a single estimator. Additionally, an ensemble model enables a machine learning method to deal with imbalanced data, which is considered to be one of the most challenging problems in machine learning. In thi...
Conference Paper
Crude oil is fundamental for global growth and stability. The factors influencing crude oil prices and more generally, the oil market, are well known to be dynamic, volatile and evolving. Subsequently, crude oil prediction is a complex and notoriously difficult task. In this paper, we evaluate the Multi-recurrent Network (MRN), a simple yet powerfu...
Chapter
Computer vision has been revolutionised in recent years by increased research in convolutional neural networks (CNNs); however, many challenges remain to be addressed in order to ensure fast and accurate image processing when applying these techniques to robotics. These challenges consist of handling extreme changes in scale, illumination, noise, a...
Code
Biotac SP sensors software
Code
CNCR Lab @ NTU - Sawyer grasping project This repository was created for using the Sawyer Robotic Arm and other parts with ROS. It has been developed on Ubuntu 16.04 and for ROS kinetic Parts This project is using : three Biotac SP sensors a right AR10 robotic hand the Sawyer robotic arm Details This repository is ROS package, providing Python l...
Code
Details Object classification using YOLO3 and an Intel RealSense D435. Requirements Documentation Biotac SP sensors with ROS integration AR 10 hand Sawyer Robot Software Ubuntu 18.04 LTS ROS Melodic librealsense2 pyrealsense 2 Hardware Intel Realsense D435 Biotac SP sensors Sawyer Robotic ARM AR 10 hand
Article
Full-text available
Joint manipulation and object exchange are common in many everyday scenarios. Although they are trivial tasks for humans, they are still very challenging for robots. Existing approaches for robot-to-human object handover assume that there is no fault during the transfer. However, unintentional perturbation forces can be occasionally applied to the...
Article
Artificial neural networks have been used as a powerful processing tool in various areas such as pattern recognition, control, robotics, and bioinformatics. Their wide applicability has encouraged researchers to improve artificial neural networks by investigating the biological brain. Neurological research has significantly progressed in recent yea...
Conference Paper
Full-text available
Computer vision has been revolutionised in recent years by increased research in convolutional neural networks (CNNs); however, many challenges remain to be addressed in order to ensure fast and accurate image processing when applying these techniques to robotics. These challenges consist of handling extreme changes in scale, illumination , noise,...
Preprint
Full-text available
Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory. Spiking neural models are distinguished from classical neurons by being biological plausible and exhibiting the same dynamics as those observed in biologic...
Chapter
Full-text available
Biological image processing is performed by complex neural networks composed of thousands of neurons interconnected via thousands of synapses, some of which are excitatory and others inhibitory. Spiking neural models are distinguished from classical neurons by being biological plausible and exhibiting the same dynamics as those observed in biologic...
Conference Paper
Full-text available
Accurate estimation of interactions in neuronal circuits is critical in understanding neural information processing and the neuronal dynamics of emergent networks. Transfer entropy(TE) is a model free information theoretic measure of flow of information between two random processes. TE has recently gained much popularity due to its effectiveness in...
Article
A common learning task for a spiking neuron is to map a spatiotemporal input pattern to a target output spike train. There is no prescribed method for selection of the target output spike train. However, the precise spiking pattern of the target output spike train (output encoding) can affect the learning performance of the spiking neuron. Therefor...
Chapter
Multi-modal data extracted from different sensors in a smart home can be fused to build models that recognize the daily living activities of residents. This paper proposes a Deep Convolutional Neural Network to perform the activity recognition task using the multi-modal data collected from a smart residential home. The dataset contains acceleromete...
Conference Paper
Full-text available
Obstacle avoidance is a critical aspect of control for a mobile robot when navigating towards a goal in an unfamiliar environment. Where traditional methods for obstacle avoidance depend heavily on path planning to reach a specific goal location whilst avoiding obstacles, the method proposed uses an adaption of a potential fields algorithm to succe...
Data
Object trajectory classification running on Embedded dedicated hardware.
Article
A Deep Boltzmann Machine is a model of a Deep Neural Network formed from multiple layers of neurons with nonlinear activation functions. The structure of a Deep Boltzmann Machine enables it to learn very complex relationships between features and facilitates advanced performance in learning of high-level representation of features, compared to conv...
Conference Paper
We have previously reported progress in developing a multilayer SAM spiking neural network and a training algorithm, suitable for implementation on an FPGA with “On-Chip Learning”. Here we report on utilization of a SAM -based network for continuous function approximation, which to date has proved difficult to achieve on a LIF type spiking neural n...
Article
Tinnitus is a problem that affects a diverse range of people. One common trait amongst tinnitus sufferers is the presence of hearing loss, which is apparent in over 90% of the cohort. It is postulated that the remainder of tinnitus sufferers have hidden hearing loss in the form of cochlear synaptopathy. The loss of hearing sensation is thought to c...
Chapter
Full-text available
Real time classification of objects using computer vision techniques are becoming relevant with emergence of advanced perceptions systems required by, surveillance systems, industry 4.0 robotics and agricultural robots. Conventional video surveillance basically detects and tracks moving object whereas there is no indication of whether the object is...
Conference Paper
The retina performs the earlier stages of image processing in living beings and is composed of six different groups of cells, namely, the rods, cones, horizontal, bipolar, amacrine and ganglion cells. Each of those group of cells can be subdivided into other types of cells that vary in shape, size, connectivity and functionality. Each cell is respo...
Conference Paper
Full-text available
Spike train synchrony estimation of neuronal cultures provides valuable insights into firing patterns of neurons in terms of degree of similarity or dissimilarity. These estimations have proven to be a useful tool in neuroscience since synchrony in neuronal networks is thought to be related to cognitive processes, sensory awareness, learning and ne...
Conference Paper
Full-text available
This paper describes the application of a Convolutional Neural Network (CNN) in the context of a predator/prey scenario. The CNN is trained and run on data from a Dynamic and Active Pixel Sensor (DAVIS) mounted on a Summit XL robot (the predator), which follows another one (the prey). The CNN is driven by both conventional image frames and dynamic...
Article
Tactile sensing has recently been used in robotics for object identification, grasping, and material identification. Although human tactile sensing is multimodal, existing tactile material recognition approaches use vibration information only. Moreover, material identification through tactile sensing can be solved as an continuous process, yet stat...
Conference Paper
Hand gestures provide a natural way for humans to interact with computers to perform a variety of different applications. However, factors such as the complexity of hand gesture structures, differences in hand size, hand posture, and environmental illumination can influence the performance of hand gesture recognition algorithms. Recent advances in...
Article
For a considerable time, it has been the goal of computational neuroscientists to understand biological nervous systems. However, the vast complexity of such systems has made it very difficult to fully understand even basic functions such as movement. Because of its small neuron count, the C. elegans nematode offers the opportunity to study a fully...
Article
A system of interacting agents is, by definition, very demanding in terms of computational resources. Although multi-agent systems have been used to solve complex problems in many areas, it is usually very difficult to perform large-scale simulations in their targeted serial computing platforms. Reconfigurable hardware, in particular Field Programm...
Conference Paper
Full-text available
A fundamental problem in cooperative Human-Robot Interaction is object handover. Existing works in this area assume the human can reliably grasp the object from the robot hand. However, in some situations the human can produce perturbing forces in the object that are not meant to end in a handover. These perturbations can result in the object being...
Article
The creation of a predictive system that correctly forecasts future changes of a stock price is crucial for investment management and algorithmic trading. The use of technical analysis for financial forecasting has been successfully employed by many researchers. Input window length is a time frame parameter required to be set when calculating many...
Poster
Full-text available
The retina is a thin peace of tissue situated at the back of the eye and it is responsible for performing the first stages of image processing [1]. It is composed of seven layers; each of these layers accommodates different cell types that are responsible for processing the visual stimuli and forwarding the processed information to the visual corte...
Article
Full-text available
[ J. R. Soc. Interface 14 , 20160902. (2016; Published 18 January). ([doi:10.1098/rsif.2016.0902][2])][2] The authors wish to correct an error in the legend to figure 1. The references stated should be [35,36,62,64] and not [27–31,35]. []: /lookup/doi/10.1098/rsif.2016.0902
Conference Paper
The nematode C. elegans (Caenorhabditis elegans) has for many years been instrumental as a model organism for fundamental research into biological neural networks, mainly to understand the behaviour and physiology of nervous systems. The Si elegans EU FP7 project aims to develop a Hardware Neural Network (HNN) to accurately replicate the C. elegans...
Conference Paper
The nematode C. elegans is the only organism to have its connectome fully documented. All 302 neurons of the worm are already known, however, their description is somewhat lacking. Using current computational techniques for clustering, such as Growing Self Organizing Networks and K-Means algorithm, this paper aims to provide a deeper analysis and u...
Conference Paper
Tactile sensing has recently attracted significant research interest in robotics. Despite the fact that tactile sensors provide temporal sequences of readings, state-of-the-art material recognition approaches are episodic, i.e. a whole sequence of readings is processed to identify the material. Based on vibration frequency response, this work prese...
Conference Paper
Understanding how simple biological entities perform complex tasks (such as moving away from predators, reproduction and seeking for food) is one of the main goals of researchers across the world. The C. elegans nematode is one of the simplest and well characterised biological nervous systems (BNS) and the Si elegans EU FP7 project aims to develop...
Poster
Full-text available
The retina is a very thin tissue, approximately half a millimeter thick, sitting at the back of the eyeball and considered an extension of the brain . Light variations, representing visual stimuli, are sensed by the photoreceptors and then passed through a series of neural connections and cells toward the surface of the retina, where the ganglion-c...
Conference Paper
Full-text available
Traditionally, it has been assumed that the important information from a visual scene is encoded within the average firing rate of a retinal ganglion cell. Many modelling techniques thus focus solely on estimating a firing rate rather than a cells temporal resp