GhostVLAD for set-based face recognition

The objective of this paper is to learn a compact representation of image sets for template-based face recognition. We make the following contributions: first, we propose a network architecture which aggregates and embeds the face descriptors produced by deep convolutional neural networks into a compact fixed-length representation. This compact representation requires minimal memory storage and enables efficient similarity computation. Second, we propose a novel GhostVLAD layer that includes {\em ghost clusters}, that do not contribute to the aggregation. We show that a quality weighting on the input faces emerges automatically such that informative images contribute more than those with low quality, and that the ghost clusters enhance the network's ability to deal with poor quality images. Third, we explore how input feature dimension, number of clusters and different training techniques affect the recognition performance. Given this analysis, we train a network that far exceeds the state-of-the-art on the IJB-B face recognition dataset. This is currently one of the most challenging public benchmarks, and we surpass the state-of-the-art on both the identification and verification protocols.Comment: Accepted by ACCV 201

Complete gradient-LC-ESI system on a chip for protein analysis

This paper presents the first fully integrated gradient-elution liquid chromatography-electrospray ionization (LC-ESI) system on a chip. This chip integrates a pair of high-pressure gradient pumps, a sample injection pump, a passive mixer, a packed separation column, and an ESI nozzle. We also present the successful on-chip separation of protein digests by reverse phase (RP)-LC coupled with on-line mass spectrometer (MS) analysis

Back to the future? A theoretically inspired musing on the concept of Product Stewardship and its implications for Corporate and Social Responsibility

yesThe concept of corporate and social responsibility (CSR) has gained increasing momentum and importance in business operations today and companies have globally responded to this philosophy. To what end though? Product Stewardship (PS) and the corporate, social and environmental responsibilities associated within this term are a key part of a business’s CSR agenda. In the extant literature, it is a challenge to clearly identify the boundaries of responsibility for PS - who sets these boundaries for governance and what are the actions taken under the guise of PS. This paper aims to start the process of demystification in responding to the title of this work, stimulate further musings and outline a future research agenda

Where are you? A preliminary examination of the track and trace mechanisms in place to facilitate effective closed-loop medical equipment retrieval in the National Health Service (NHS) (UK)

yesThe National Health Service (UK) is wholly accountable and heavily scrutinised for its strategy, activity, performance and spending (Appleby, 2016; NHS Confederation, 2016; Parliament UK, 2010), and much research has been undertaken as to its effectiveness at managing its operations and its competency in doing so (Gov.Uk, 2016; National Audit Office, 1999)). The impact of not performing adequately combined with threats such as funding cuts (King’s Fund, 2016), government intervention and private sector competition; has led to uncertainty and disillusion with the sustainability of the service (Hunter, 2016). Based on current economic concerns, this paper chooses to focus on the area of Medical Equipment Loans Services where products are released to patients to aid therapeutic rehabilitation and physical mobility. The aim of this study is to examine the process of product retrieval in a multi-case study analysis and consider how value-added technologies can be used to improve retrieval success rates