Queensland University of Technology

About: Queensland University of Technology is a education organization based out in Brisbane, Queensland, Australia. It is known for research contribution in the topics: Population & Context (language use). The organization has 14188 authors who have published 55022 publications receiving 1496237 citations. The organization is also known as: QUT.

Iris Recognition With Off-the-Shelf CNN Features: A Deep Learning Perspective

Abstract: Iris recognition refers to the automated process of recognizing individuals based on their iris patterns. The seemingly stochastic nature of the iris stroma makes it a distinctive cue for biometric recognition. The textural nuances of an individual’s iris pattern can be effectively extracted and encoded by projecting them onto Gabor wavelets and transforming the ensuing phasor response into a binary code - a technique pioneered by Daugman. This textural descriptor has been observed to be a robust feature descriptor with very low false match rates and low computational complexity. However, recent advancements in deep learning and computer vision indicate that generic descriptors extracted using convolutional neural networks (CNNs) are able to represent complex image characteristics. Given the superior performance of CNNs on the ImageNet large scale visual recognition challenge and a large number of other computer vision tasks, in this paper, we explore the performance of state-of-the-art pre-trained CNNs on iris recognition. We show that the off-the-shelf CNN features, while originally trained for classifying generic objects, are also extremely good at representing iris images, effectively extracting discriminative visual features and achieving promising recognition results on two iris datasets: ND-CrossSensor-2013 and CASIA-Iris-Thousand. We also discuss the challenges and future research directions in leveraging deep learning methods for the problem of iris recognition.

The horizon of materiobiology: A perspective on material-guided cell behaviors and tissue engineering

Abstract: Although the biological functions of cell and tissue can be regulated by biochemical factors (e.g., growth factors, hormones), the biophysical effects of materials on the regulation of biological activity are receiving more attention. In this Review, we systematically summarize the recent progress on how biomaterials with controllable properties (e.g., compositional/degradable dynamics, mechanical properties, 2D topography, and 3D geometry) can regulate cell behaviors (e.g., cell adhesion, spreading, proliferation, cell alignment, and the differentiation or self-maintenance of stem cells) and tissue/organ functions. How the biophysical features of materials influence tissue/organ regeneration have been elucidated. Current challenges and a perspective on the development of novel materials that can modulate specific biological functions are discussed. The interdependent relationship between biomaterials and biology leads us to propose the concept of “materiobiology”, which is a scientific discipline that studies the biological effects of the properties of biomaterials on biological functions at cell, tissue, organ, and the whole organism levels. This Review highlights that it is more important to develop ECM-mimicking biomaterials having a self-regenerative capacity to stimulate tissue regeneration, instead of attempting to recreate the complexity of living tissues or tissue constructs ex vivo. The principles of materiobiology may benefit the development of novel biomaterials providing combinative bioactive cues to activate the migration of stem cells from endogenous reservoirs (i.e., cell niches), stimulate robust and scalable self-healing mechanisms, and unlock the body’s innate powers of regeneration.

Beyond the user: use and non-use in HCI

Abstract: For many, an interest in Human-Computer Interaction is equivalent to an interest in usability. However, using computers is only one way of relating to them, and only one topic from which we can learn about interactions between people and technology. Here, we focus on not using computers -- ways not to use them, aspects of not using them, what not using them might mean, and what we might learn by examining non-use as seriously as we examine use.