41,529 research outputs found
DeepMarks: A Digital Fingerprinting Framework for Deep Neural Networks
This paper proposes DeepMarks, a novel end-to-end framework for systematic
fingerprinting in the context of Deep Learning (DL). Remarkable progress has
been made in the area of deep learning. Sharing the trained DL models has
become a trend that is ubiquitous in various fields ranging from biomedical
diagnosis to stock prediction. As the availability and popularity of
pre-trained models are increasing, it is critical to protect the Intellectual
Property (IP) of the model owner. DeepMarks introduces the first fingerprinting
methodology that enables the model owner to embed unique fingerprints within
the parameters (weights) of her model and later identify undesired usages of
her distributed models. The proposed framework embeds the fingerprints in the
Probability Density Function (pdf) of trainable weights by leveraging the extra
capacity available in contemporary DL models. DeepMarks is robust against
fingerprints collusion as well as network transformation attacks, including
model compression and model fine-tuning. Extensive proof-of-concept evaluations
on MNIST and CIFAR10 datasets, as well as a wide variety of deep neural
networks architectures such as Wide Residual Networks (WRNs) and Convolutional
Neural Networks (CNNs), corroborate the effectiveness and robustness of
DeepMarks framework
Mathematical and computer modeling of electro-optic systems using a generic modeling approach
The conventional approach to modelling electro-optic sensor systems is to develop separate models for individual systems or classes of system, depending on the detector technology employed in the sensor and the application. However, this ignores commonality in design and in components of these systems. A generic approach is presented for modelling a variety of sensor systems operating in the infrared waveband that also allows systems to be modelled with different levels of detail and at different stages of the product lifecycle. The provision of different model types (parametric and image-flow descriptions) within the generic framework can allow valuable insights to be gained
A sub-mW IoT-endnode for always-on visual monitoring and smart triggering
This work presents a fully-programmable Internet of Things (IoT) visual
sensing node that targets sub-mW power consumption in always-on monitoring
scenarios. The system features a spatial-contrast binary
pixel imager with focal-plane processing. The sensor, when working at its
lowest power mode ( at 10 fps), provides as output the number of
changed pixels. Based on this information, a dedicated camera interface,
implemented on a low-power FPGA, wakes up an ultra-low-power parallel
processing unit to extract context-aware visual information. We evaluate the
smart sensor on three always-on visual triggering application scenarios.
Triggering accuracy comparable to RGB image sensors is achieved at nominal
lighting conditions, while consuming an average power between and
, depending on context activity. The digital sub-system is extremely
flexible, thanks to a fully-programmable digital signal processing engine, but
still achieves 19x lower power consumption compared to MCU-based cameras with
significantly lower on-board computing capabilities.Comment: 11 pages, 9 figures, submitteted to IEEE IoT Journa
The Accessible Toilet Design Resource
This Accessible Toilet Design Resource has been produced from new primary research carried out within VivaCity 2020, a large university-based research consortium that is developing tools and resources to support the design of socially inclusive cities. The consortium is funded by the Engineering and Physical Sciences Research Council (EPSRC). It was set up in 2003 and will complete its work in 2008. The Resource is concerned primarily with the design of the accessible toilet cubicle that should be provided for customer or public use wherever there is standard toilet provision. Though it may make reference to other types of toilet cubicles, urinals, automatic public conveniences (APCs) or grouped toilet provision, the location and design of these facilities are not addressed in great detail here. The location and design of accessible toilet facilities merits this independent, detailed scrutiny because it is essential to provide these facilities and to design them correctly, so that disabled people can participate on equal terms to able-bodied people in every aspect of city life
Project OASIS: The Design of a Signal Detector for the Search for Extraterrestrial Intelligence
An 8 million channel spectrum analyzer (MCSA) was designed the meet to meet the needs of a SETI program. The MCSA puts out a very large data base at very high rates. The development of a device which follows the MCSA, is presented
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