Reflective band image generation in the night vision integrated performance model

2016 ◽  
Author(s):  
Brian P. Teaney ◽  
Joseph P. Reynolds
2015 ◽  
Author(s):  
Brian P. Teaney ◽  
Joseph P. Reynolds ◽  
Todd W. Du Bosq ◽  
Endre Repasi

2014 ◽  
Author(s):  
Kevin R. Leonard ◽  
Van Hodgkin ◽  
Bradley Preece ◽  
Roger Thompson ◽  
Keith Krapels

2014 ◽  
Author(s):  
David P. Haefner ◽  
Jonathan D. Fanning ◽  
Brian P. Teaney ◽  
Stephen D. Burks

2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Peng Liu ◽  
Fuyu Li ◽  
Shanshan Yuan ◽  
Wanyi Li

Object detection in thermal images is an important computer vision task and has many applications such as unmanned vehicles, robotics, surveillance, and night vision. Deep learning-based detectors have achieved major progress, which usually need large amount of labelled training data. However, labelled data for object detection in thermal images is scarce and expensive to collect. How to take advantage of the large number labelled visible images and adapt them into thermal image domain is expected to solve. This paper proposes an unsupervised image-generation enhanced adaptation method for object detection in thermal images. To reduce the gap between visible domain and thermal domain, the proposed method manages to generate simulated fake thermal images that are similar to the target images and preserves the annotation information of the visible source domain. The image generation includes a CycleGAN-based image-to-image translation and an intensity inversion transformation. Generated fake thermal images are used as renewed source domain, and then the off-the-shelf domain adaptive faster RCNN is utilized to reduce the gap between the generated intermediate domain and the thermal target domain. Experiments demonstrate the effectiveness and superiority of the proposed method.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ekpenyong Ekpenyong Udofia ◽  
Bimbo Onaolapo Adejare ◽  
Gbemi Oladipo Olaore ◽  
Etete Ekpenyong Udofia

PurposeMost studies on small and medium scale enterprises lump both small-scale and medium-scale businesses together as entirely similar phenomenon, thus creating an oversight of the degree of performance recorded by medium-scale businesses. In line with investigating medium-scale firms' performance, this study examines the role of quality management in the performance of medium-scale firms to evolve research-based recommendation for better performance.Design/methodology/approachCross-sectional survey design and random sampling were employed. Analysis was based on 915 responses obtained via questionnaire copy distribution from employees within the supply chain, production, operations, and marketing/sales department of selected firms. Hypotheses testing was done using the structural equation model.FindingsA positive significant relationship between quality management and operational performance, employee performance, and quality performance dimensions was identified. An insignificant relationship between quality management and financial and innovation performance dimensions was discovered. However, when mediated by employee focus and process management, significant relationships were observed among all performance dimensions.Research limitations/implicationsThe study reveals that employee focus and process management have the greatest mediating impact on the relationship between quality management and the organisational performance of medium-scale manufacturing firms. This study charts the course for other studies to investigate the mediating role of quality management practices on the relationship between quality management and the organisational performance of medium-scale firms in other developing nations. The manufacturing sector has thirteen industries, but only six were captured in this study. This poses a limitation to the generalisation of the findings of this study. Further studies could strive for a representation of every manufacturing industry to aid generalisation purposes.Practical implicationsManagers of medium-scale manufacturing firms must understand that it might be impossible to get a one size fits all approach to improving performance dimensions. Managers are advised to choose one or two performance dimensions as the goal, then focus on achieving them. This will help clarify which path is best to get the desired results and maximise their quality management system.Originality/valueThis study examines the impact of quality management practices on an integrated performance model of medium-scale firms. The study also uniquely examines the mediating impact of exclusive quality management practices on the relationship between quality management and an integrated performance model.


1982 ◽  
Author(s):  
C. Hoover ◽  
J. Ratches ◽  
F. Shields ◽  
K. Mayo

Sign in / Sign up

Export Citation Format

Share Document