1,720,959 research outputs found
Running hardware-aware neural architecture search on embedded devices under 512MB of RAM
No full textColab NAS: Obtaining lightweight task-specific convolutional neural networks following Occam's razor
Full text linkThe current trend of applying transfer learning from convolutional neural
networks (CNNs) trained on large datasets can be an overkill when the target
application is a custom and delimited problem, with enough data to train a
network from scratch. On the other hand, the training of custom and lighter
CNNs requires expertise, in the from-scratch case, and or high-end resources,
as in the case of hardware-aware neural architecture search (HW NAS), limiting
access to the technology by non-habitual NN developers.
For this reason, we present ColabNAS, an affordable HW NAS technique for
producing lightweight task-specific CNNs. Its novel derivative-free search
strategy, inspired by Occam's razor, allows to obtain state-of-the-art results
on the Visual Wake Word dataset, a standard TinyML benchmark, in just 3.1 GPU
hours using free online GPU services such as Google Colaboratory and Kaggle
Kernel
Human recognition for resource constrained mobile robot applied to Covid-19 Disinfection
No full textThe global COVID-19 pandemic has stimulated the production of disinfection robots by institutions and companies. The concept of automated disinfection without involving human operators looks interesting in the eyes of the hospital management, and not only. It can save lives by avoiding the cleaning staff working in highly infected environments. At the same time, it can reduce costs by diminishing staff.
The most commonly adopted robots, like the one from the UVD company, use UV-C light to disinfect surfaces. UV-C radiations alter DNA and RNA so that organisms cannot replicate. Others use also vapor and fogging systems that spray chemical disinfectants, such as ozone.
However, UV-C lamps strongly limit human-machine cooperation. Direct exposure to UV-C radiation to the skin has to be avoided for health reasons.
Fortunately, the outstanding results of machine learning offer new possibilities for robotics automation. It can be used to deeply understand the outside world and take actions accordingly, shutting down the lamps whenever a human is detected. So that human-machine cooperation is enabled
Leveraging systems’ non-linearity to tackle the scarcity of data in the design of intelligent fault diagnosis systems
Full text linkDeep transfer learning (DTL) allows for the efficient building of intelligent fault diagnosis systems (IFDS). On the other hand, DTL methods still heavily rely on large amounts of labelled data. Obtaining such an amount of data can be challenging when dealing with machines or structures faults. This document proposes a novel approach to the design of vibration-based IFDS using DTL in condition of strong data scarcity. A periodic multi-excitation level procedure leveraging intrinsic non-linearities of real-world systems is used to produce images that can be conveniently analysed by pre-trained Convolutional Neural Networks to diagnose faults. A new data visualization method and its augmentation technique are proposed in this paper to tackle the typical lack of data encountered during the design of IFDS. Experimental validation on a railway pantograph structure provides effective support for the proposed method
An Affordable Hardware-Aware Neural Architecture Search for Deploying Convolutional Neural Networks on Ultra-Low-Power Computing Platforms
No full textHardware-aware neural architecture search (HW-NAS) allows the integration of convolutional neural networks (CNNs) in microcontrollers devices by automatically designing neural architectures that can fit prearranged hardware constraints. However, state-of-the-art HW-NAS target high-performance microcontrollers, whose power consumption does not meet sensing nodes requirements. This letter presents a HW-NAS generating tiny CNNs that can run on ultra-low-power microcontrollers, featuring a lightweight search procedure enabling its execution even on embedded devices. Empirical results on three well-known benchmarks for tiny computer vision proved that the proposed HW-NAS was able to generate tiny CNNs while preserving state-of-the-art classification accuracy
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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