ORCID Profile
0000-0002-7448-2327
Current Organisations
Edith Cowan University
,
University of Western Australia
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2018
Publisher: Springer Science and Business Media LLC
Date: 26-08-2021
Publisher: Springer Berlin Heidelberg
Date: 2011
Publisher: Springer Science and Business Media LLC
Date: 16-01-2020
DOI: 10.1038/S41398-020-0695-Z
Abstract: Autism spectrum disorder is a heritable neurodevelopmental condition diagnosed based on social and communication differences. There is strong evidence that cognitive and behavioural changes associated with clinical autism aggregate with biological relatives but in milder form, commonly referred to as the ‘broad autism phenotype’. The present study builds on our previous findings of increased facial masculinity in autistic children (Sci. Rep., 7:9348, 2017) by examining whether facial masculinity represents as a broad autism phenotype in 55 non-autistic siblings (25 girls) of autistic children. Using 3D facial photogrammetry and age-matched control groups of children without a family history of ASD, we found that facial features of male siblings were more masculine than those of male controls ( n = 69 p 0.001, d = 0.81 [0.36, 1.26]). Facial features of female siblings were also more masculine than the features of female controls ( n = 60 p = 0.005, d = 0.63 [0.16, 1.10]). Overall, we demonstrated for males and females that facial masculinity in non-autistic siblings is increased compared to same-sex comparison groups. These data provide the first evidence for a broad autism phenotype expressed in a physical characteristic, which has wider implications for our understanding of the interplay between physical and cognitive development in humans.
Publisher: IEEE
Date: 11-2016
Publisher: Elsevier BV
Date: 11-2020
Publisher: Springer Science and Business Media LLC
Date: 15-04-2015
Publisher: IEEE
Date: 06-2015
Publisher: The Royal Society
Date: 07-10-2015
Abstract: Prenatal testosterone may have a powerful masculinizing effect on postnatal physical characteristics. However, no study has directly tested this hypothesis. Here, we report a 20-year follow-up study that measured testosterone concentrations from the umbilical cord blood of 97 male and 86 female newborns, and procured three-dimensional facial images on these participants in adulthood (range: 21–24 years). Twenty-three Euclidean and geodesic distances were measured from the facial images and an algorithm identified a set of six distances that most effectively distinguished adult males from females. From these distances, a ‘gender score’ was calculated for each face, indicating the degree of masculinity or femininity. Higher cord testosterone levels were associated with masculinized facial features when males and females were analysed together ( n = 183 r = −0.59), as well as when males ( n = 86 r = −0.55) and females ( n = 97 r = −0.48) were examined separately ( p -values 0.001). The relationships remained significant and substantial after adjusting for potentially confounding variables. Adult circulating testosterone concentrations were available for males but showed no statistically significant relationship with gendered facial morphology ( n = 85, r = 0.01, p = 0.93). This study provides the first direct evidence of a link between prenatal testosterone exposure and human facial structure.
Publisher: IEEE
Date: 11-2013
Publisher: The Royal Society
Date: 23-03-2022
Abstract: The broad autism phenotype commonly refers to sub-clinical levels of autistic-like behaviour and cognition presented in biological relatives of autistic people. In a recent study, we reported findings suggesting that the broad autism phenotype may also be expressed in facial morphology, specifically increased facial masculinity. Increased facial masculinity has been reported among autistic children, as well as their non-autistic siblings. The present study builds on our previous findings by investigating the presence of increased facial masculinity among non-autistic parents of autistic children. Using a previously established method, a ‘facial masculinity score’ and several facial distances were calculated for each three-dimensional facial image of 192 parents of autistic children (58 males, 134 females) and 163 age-matched parents of non-autistic children (50 males, 113 females). While controlling for facial area and age, significantly higher masculinity scores and larger (more masculine) facial distances were observed in parents of autistic children relative to the comparison group, with effect sizes ranging from small to medium (0.16 ≤ d ≤ .41), regardless of sex. These findings add to an accumulating evidence base that the broad autism phenotype is expressed in physical characteristics and suggest that both maternal and paternal pathways are implicated in masculinized facial morphology.
Publisher: American Academy of Sleep Medicine (AASM)
Date: 15-04-2020
DOI: 10.5664/JCSM.8246
Publisher: Wiley
Date: 16-09-2021
DOI: 10.1002/AUR.2612
Abstract: Greater facial asymmetry has been consistently found in children with autism spectrum disorder (ASD) relative to children without ASD. There is substantial evidence that both facial structure and the recurrence of ASD diagnosis are highly heritable within a nuclear family. Furthermore, sub‐clinical levels of autistic‐like behavioural characteristics have also been reported in first‐degree relatives of in iduals with ASD, commonly known as the ‘broad autism phenotype’. Therefore, the aim of the current study was to examine whether a broad autism phenotype expresses as facial asymmetry among 192 biological parents of autistic in iduals (134 mothers) compared to those of 163 age‐matched adults without a family history of ASD (113 females). Using dense surface‐modelling techniques on three dimensional facial images, we found evidence for greater facial asymmetry in parents of autistic in iduals compared to age‐matched adults in the comparison group ( p = 0.046, d = 0.21 [0.002, 0.42]). Considering previous findings and the current results, we conclude that facial asymmetry expressed in the facial morphology of autistic children may be related to heritability factors. In a previous study, we showed that autistic children presented with greater facial asymmetry than non‐autistic children. In the current study, we examined the amount of facial asymmetry shown on three‐dimensional facial images of 192 parents of autistic children compared to a control group consisting of 163 similarly aged adults with no known history of autism. Although parents did show greater levels of facial asymmetry than those in the control group, this effect is statistically small. We concluded that the facial asymmetry previously found in autistic children may be related to genetic factors.
Publisher: IEEE
Date: 08-2014
Publisher: IEEE
Date: 06-2018
Publisher: IEEE
Date: 03-2014
Publisher: Springer International Publishing
Date: 2018
Publisher: Wiley
Date: 30-10-2023
DOI: 10.1002/JBMR.4921
Publisher: Springer Berlin Heidelberg
Date: 2009
Publisher: Public Library of Science (PLoS)
Date: 12-06-2014
Publisher: MDPI AG
Date: 04-12-2020
DOI: 10.3390/S20236941
Abstract: Detecting key frames in videos is a common problem in many applications such as video classification, action recognition and video summarization. These tasks can be performed more efficiently using only a handful of key frames rather than the full video. Existing key frame detection approaches are mostly designed for supervised learning and require manual labelling of key frames in a large corpus of training data to train the models. Labelling requires human annotators from different backgrounds to annotate key frames in videos which is not only expensive and time consuming but also prone to subjective errors and inconsistencies between the labelers. To overcome these problems, we propose an automatic self-supervised method for detecting key frames in a video. Our method comprises a two-stream ConvNet and a novel automatic annotation architecture able to reliably annotate key frames in a video for self-supervised learning of the ConvNet. The proposed ConvNet learns deep appearance and motion features to detect frames that are unique. The trained network is then able to detect key frames in test videos. Extensive experiments on UCF101 human action and video summarization VSUMM datasets demonstrates the effectiveness of our proposed method.
Publisher: Springer Science and Business Media LLC
Date: 12-07-2021
Publisher: IEEE
Date: 12-2019
Publisher: Springer Science and Business Media LLC
Date: 24-08-2017
DOI: 10.1038/S41598-017-09939-Y
Abstract: Elevated prenatal testosterone exposure has been associated with Autism Spectrum Disorder (ASD) and facial masculinity. By employing three-dimensional (3D) photogrammetry, the current study investigated whether prepubescent boys and girls with ASD present increased facial masculinity compared to typically-developing controls. There were two phases to this research. 3D facial images were obtained from a normative s le of 48 boys and 53 girls (3.01–12.44 years old) to determine typical facial masculinity/femininity. The sexually dimorphic features were used to create a continuous ‘gender score’, indexing degree of facial masculinity. Gender scores based on 3D facial images were then compared for 54 autistic and 54 control boys (3.01–12.52 years old), and also for 20 autistic and 60 control girls (4.24–11.78 years). For each sex, increased facial masculinity was observed in the ASD group relative to control group. Further analyses revealed that increased facial masculinity in the ASD group correlated with more social-communication difficulties based on the Social Affect score derived from the Autism Diagnostic Observation Scale-Generic (ADOS-G). There was no association between facial masculinity and the derived Restricted and Repetitive Behaviours score. This is the first study demonstrating facial hypermasculinisation in ASD and its relationship to social-communication difficulties in prepubescent children.
Publisher: MDPI AG
Date: 20-11-2020
DOI: 10.3390/S20226647
Abstract: Convolutional neural networks have recently been used for multi-focus image fusion. However, some existing methods have resorted to adding Gaussian blur to focused images, to simulate defocus, thereby generating data (with ground-truth) for supervised learning. Moreover, they classify pixels as ‘focused’ or ‘defocused’, and use the classified results to construct the fusion weight maps. This then necessitates a series of post-processing steps. In this paper, we present an end-to-end learning approach for directly predicting the fully focused output image from multi-focus input image pairs. The suggested approach uses a CNN architecture trained to perform fusion, without the need for ground truth fused images. The CNN exploits the image structural similarity (SSIM) to calculate the loss, a metric that is widely accepted for fused image quality evaluation. What is more, we also use the standard deviation of a local window of the image to automatically estimate the importance of the source images in the final fused image when designing the loss function. Our network can accept images of variable sizes and hence, we are able to utilize real benchmark datasets, instead of simulated ones, to train our network. The model is a feed-forward, fully convolutional neural network that can process images of variable sizes during test time. Extensive evaluation on benchmark datasets show that our method outperforms, or is comparable with, existing state-of-the-art techniques on both objective and subjective benchmarks.
Publisher: Wiley
Date: 21-06-2019
DOI: 10.1002/AUR.2161
Abstract: A key research priority in the study of autism spectrum conditions (ASC) is the discovery of biological markers that may help to identify and elucidate etiologically distinct subgroups. One physical marker that has received increasing research attention is facial structure. Although there remains little consensus in the field, findings relating to greater facial asymmetry (FA) in ASC exhibit some consistency. As there is growing recognition of the importance of replicatory studies in ASC research, the aim of this study was to investigate the replicability of increased FA in autistic children compared to nonautistic peers. Using three-dimensional photogrammetry, this study examined FA in 84 autistic children, 110 typically developing children with no family history of the condition, and 49 full siblings of autistic children. In support of previous literature, significantly greater depth-wise FA was identified in autistic children relative to the two comparison groups. As a further investigation, increased lateral FA in autistic children was found to be associated with greater severity of ASC symptoms on the Autism Diagnostic Observation Schedule, second edition, specifically related to repetitive and restrictive behaviors. These outcomes provide an important and independent replication of increased FA in ASC, as well as a novel contribution to the field. Having confirmed the direction and areas of increased FA in ASC, these findings could motivate a search for potential underlying brain dysmorphogenesis. Autism Res 2019, 12: 1774-1783. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study looked at the amount of facial asymmetry (FA) in autistic children compared to typically developing children and children who have siblings with autism. The study found that autistic children, compared to the other two groups, had greater FA, and that increased FA was related to greater severity of autistic symptoms. The face and brain grow together during the earliest stages of development, and so findings of facial differences in autism might inform future studies of early brain differences associated with the condition.
Publisher: Elsevier BV
Date: 09-2017
Publisher: IEEE
Date: 2009
Publisher: Association for Computing Machinery (ACM)
Date: 16-10-2019
DOI: 10.1145/3355390
Abstract: Video description is the automatic generation of natural language sentences that describe the contents of a given video. It has applications in human-robot interaction, helping the visually impaired and video subtitling. The past few years have seen a surge of research in this area due to the unprecedented success of deep learning in computer vision and natural language processing. Numerous methods, datasets, and evaluation metrics have been proposed in the literature, calling the need for a comprehensive survey to focus research efforts in this flourishing new direction. This article fills the gap by surveying the state-of-the-art approaches with a focus on deep learning models comparing benchmark datasets in terms of their domains, number of classes, and repository size and identifying the pros and cons of various evaluation metrics, such as SPICE, CIDEr, ROUGE, BLEU, METEOR, and WMD. Classical video description approaches combined subject, object, and verb detection with template-based language models to generate sentences. However, the release of large datasets revealed that these methods cannot cope with the ersity in unconstrained open domain videos. Classical approaches were followed by a very short era of statistical methods that were soon replaced with deep learning, the current state-of-the-art in video description. Our survey shows that despite the fast-paced developments, video description research is still in its infancy due to the following reasons: Analysis of video description models is challenging, because it is difficult to ascertain the contributions towards accuracy or errors of the visual features and the adopted language model in the final description. Existing datasets neither contain adequate visual ersity nor complexity of linguistic structures. Finally, current evaluation metrics fall short of measuring the agreement between machine-generated descriptions with that of humans. We conclude our survey by listing promising future research directions.
Publisher: IEEE
Date: 06-2019
Publisher: Springer Nature Switzerland
Date: 2022
Publisher: Springer Nature Switzerland
Date: 2023
No related grants have been discovered for Syed Zulqarnain Gilani.