Yona Falinie Abdul Gaus

Yona Falinie Abdul Gaus
Durham University | DU · Department of Computer Science

PDRA

About

34
Publications
16,595
Reads
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344
Citations
Introduction
Phd survivor with quantitative background and experience in image processing, image retrieval, analytics, statistics, machine learning, cognitive and behavioral sciences. Passionate about using big data and quantitative modelling to bridge the gap between human-human interaction/human-computer interaction analyses.
Additional affiliations
March 2018 - present
Durham University
Position
  • PDRA

Publications

Publications (34)
Preprint
Lossy image compression strategies allow for more efficient storage and transmission of data by encoding data to a reduced form. This is essential enable training with larger datasets on less storage-equipped environments. However, such compression can cause severe decline in performance of deep Convolution Neural Network (CNN) architectures even w...
Conference Paper
The recent advancement in deep Convolutional Neural Network (CNN) has brought insight into the automation of X-ray security screening for aviation security and beyond. Here, we explore the viability of two recent end-to-end object detection CNN architectures, Cascade R-CNN and FreeAnchor, for prohibited item detection by balancing processing time a...
Preprint
Full-text available
The recent advancement in deep Convolutional Neural Network (CNN) has brought insight into the automation of X-ray security screening for aviation security and beyond. Here, we explore the viability of two recent end-to-end object detection CNN architectures, Cascade R-CNN and FreeAnchor, for prohibited item detection by balancing processing time a...
Conference Paper
Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited item detection focus primarily on pseudo-colour (rgb) X-ray imagery. In this work we study the impact of variant X-ray imagery, i.e., X-ray energy response (high, low})...
Preprint
Full-text available
Automatic detection of prohibited items within complex and cluttered X-ray security imagery is essential to maintaining transport security, where prior work on automatic prohibited item detection focus primarily on pseudo-colour (rgb}) X-ray imagery. In this work we study the impact of variant X-ray imagery, i.e., X-ray energy response (high, low})...
Preprint
Full-text available
X-ray imagery security screening is essential to maintaining transport security against a varying profile of threat or prohibited items. Particular interest lies in the automatic detection and classification of weapons such as firearms and knives within complex and cluttered X-ray security imagery. Here, we address this problem by exploring various...
Preprint
Full-text available
X-ray security screening is in widespread use to maintain transportation security against a wide range of potential threat profiles. Of particular interest is the recent focus on the use of automated screening approaches, including the potential anomaly detection as a methodology for concealment detection within complex electronic items. Here we ad...
Conference Paper
X-ray imagery security screening is essential to maintaining transport security against a varying profile of threat items. Particular interest lies in the automatic detection and classification of weapons such as firearms and knives within complex and cluttered X-ray security imagery. Here, we address this problem by exploring various end-to-end ob...
Conference Paper
X-ray imagery security screening is essential to maintaining transport security against a varying profile of prohibited items. Particular interest lies in the automatic detection and classification of prohibited items such as firearms and firearm components within complex and cluttered X-ray security imagery. We address this problem by exploring va...
Conference Paper
X-ray security screening is in widespread use to maintain transportation security against a wide range of potential threat profiles. Of particular interest is the recent focus on the use of automated screening approaches, including the potential anomaly detection as a methodology for concealment detection within complex electronic items. Here we ad...
Conference Paper
X-ray baggage security screening is widely used to maintain aviation and transport safety and security. To address the future challenges of increasing volumes and complexities, the recent focus on the use of automated screening approaches are of particular interest. This includes the potential for automatic threat detection as a methodology for con...
Preprint
Full-text available
Detecting prohibited items in X-ray security imagery is pivotal in maintaining border and transport security against a wide range of threat profiles. Convolutional Neural Networks (CNN) with the support of a significant volume of data have brought advancement in such automated prohibited object detection and classification. However, collating such...
Conference Paper
Full-text available
Detecting prohibited items in X-ray security imagery is pivotal in order to maintain border and transport security against a wide range of threat profiles. Convolutional neural networks (CNN) with the support of a significant volume of data have brought advancement in such automated prohibited object detection and classification. Collating such lar...
Preprint
Full-text available
X-ray baggage security screening is widely used to maintain aviation and transport security. Of particular interest is the focus on automated security X-ray analysis for particular classes of object such as electronics, electrical items, and liquids. However, manual inspection of such items is challenging when dealing with potentially anomalous ite...
Article
Full-text available
With the rapid development of augmented reality (AR) and virtual reality (VR) technology, human-computer interaction (HCI) has been greatly improved for gaming interaction of AR and VR control. The finger micro-gesture is one of the important interactive methods for HCI applications such as in the Google Soli and Microsoft Kinect projects. However,...
Article
Full-text available
A human being’s cognitive system can be simulated by artificial intelligent systems. Machines and robots equipped with cognitive capability can automatically recognize a humans mental state through their gestures and facial expressions. In this paper, an artificial intelligent system is proposed to monitor depression. It can predict the scales of B...
Poster
Full-text available
Mental health problem affect one in four citizen at some point of their lives. However, the first step aimed at the behaviour of people suffering from mood disorder only limited to categorize emotion description such as happy, sad, fear, surprise and so on. Our approach is to advance emotion recognition by modelling behavioural cues of human affect...
Conference Paper
Full-text available
This paper describes our working approach for the Emotional Impact of Movies task of MediaEval 2016. There are 2 sub-tasks set to make affective predictions, based on Arousal and Valence values, on video clips. Sub-task 1 requires global emotion prediction. Here a framework is developed using Deep Auto-Encoders, a feature variation algorithm and a...
Conference Paper
Full-text available
Touch is a primary nonverbal communication channel used to communicate emotions or other social messages. Despite its importance, this channel is still very little explored in the affective computing field, as much more focus has been placed on visual and aural channels. In this paper, we investigate the possibility to automatically discriminate be...
Conference Paper
Full-text available
Abstract: Automatic affective dimension recognition from facial expression continuously in naturalistic contexts is a very challenging research topic but very important in human-computer interaction. In this paper, an automatic recognition system was proposed to predict the affective dimensions such as Arousal, Valence and Dominance continuously in...
Conference Paper
Full-text available
Depression is a state of low mood and aversion to activity that can affect a person's thoughts, behavior, feelings and sense of well-being. In such a low mood, both the facial expression and voice appear different from the ones in normal states. In this paper, an automatic system is proposed to predict the scales of Beck Depression Inventory from n...
Conference Paper
The main purpose of human pose estimation is to estimate the size, position or orientation of the human body parts within the digital scene information. The estimation technique is directly influenced by the type of image feature to be used, its model representation and also the application of the system. This work focuses on estimating the size an...
Conference Paper
This paper presents a method of gesture recognition using Hidden Markov Model (HMM). Gesture itself is based on the movement of each right hand (RH) and left hand (LH), which represents the word intended by the signer. The feature vector selected, gesture path, hand distance and hand orientations are obtained from RH and LH then trained using HMM t...
Article
Full-text available
In this paper, extraction of suitable feature vector as well as the analysis and performance comparison of the feature vectors using Hidden Markov Model (HMM) are presented. Extracting suitable features comprising of centroids, hand distance and hand orientations is a necessary step to represent isolated Malaysian Sign Language (MSL) to enable dete...
Article
This work presents the development of a software-based Malaysian Sign Language recognition system using Hidden Markov Model. Ninety different gestures are used and tested in this system. Skin segmentation based on YCbCr colour space is implemented in the sign gesture videos to separate the face and hands from the background. The feature vector of s...
Conference Paper
In this paper, we introduce a hand gesture recognition system to recognize isolated Malaysian Sign Language (MSL). The system consists of four modules: collection of input images, feature extraction, Hidden Markov Model (HMM) training, and gesture recognition. First, we apply skin segmentation procedure throughout the input frames in order to detec...
Conference Paper
In this paper, a method to identify hand gesture trajectory in constrained environment is introduced. The method consists of three modules: collection of input images, skin segmentation and feature extraction. To reduce processing time, we compare the absolute difference between two consecutive frames then choose which frames have the highest value...