1,720,956 research outputs found
Battery-Less Face Recognition at the Extreme Edge
No full textMachine learning-based face recognition systems are commonly used in mobile platforms to assist the camera systems, unlock the device, or analyze the facial expressions. The computational complexity of the underlying algorithms as well as the power consumption of the entire imaging and processing system largely limit the deployment to powerful mobile processing systems with large rechargeable batteries. However, these computer vision capabilities would also be useful in miniaturized low power applications with stringent battery-size limitations. We assess the feasibility of such a computer vision edge processing system on a battery-less credit card-sized demonstrator using an ultra-low power image sensor and a machine learning system-on-chip, achieving self-sustainable operation using solar energy harvesting with a small on-board solar cell. The tested system enables continuous 1 frame-per-second battery-less imaging and face recognition in indoor lighting conditions
Improving Memory Utilization in Convolutional Neural Network Accelerators
No full textWhile the accuracy of convolutional neural networks has achieved vast improvements by introducing larger and deeper network architectures, also the memory footprint for storing their parameters and activations has increased. This trend especially challenges power-and resource-limited accelerator designs, which are often restricted to store all network data in on-chip memory to avoid interfacing energy-hungry external memories. Maximizing the network size that fits on a given accelerator thus requires to maximize its memory utilization. While the traditionally used pingpong buffering technique is mapping subsequent activation layers to disjunctive memory regions, we propose a mapping method that allows these regions to overlap and thus utilize the memory more efficiently. This work presents the mathematical model to compute the maximum activations memory overlap and thus the lower bound of on-chip memory needed to perform layer-by-layer processing of convolutional neural networks on memory-limited accelerators. Our experiments with various real-world object detector networks show that the proposed mapping technique can decrease the activations memory by up to 32.9%, reducing the overall memory for the entire network by up to 23.9% compared to traditional pingpong buffering. For higher resolution de-noising networks, we achieve activation memory savings of 48.8%. Additionally, we implement a face detector network on an FPGA-based camera to validate these memory savings on a complete end-to-end system
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
A Sub-mW Dual-Engine ML Inference System-on-Chip for Complete End-to-End Face-Analysis at the Edge
No full textSmart vision-based IoT applications operate on a sub-mW power budget while requiring power-hungry always-on image processing capabilities. This work presents a system-on-chip (SoC) that enables hierarchical processing of face analysis under multiple sub-mW operating scenarios using two tightly coupled machine learning (ML) accelerators. A dynamically scalable binary decision tree (BDT) engine for face detection (FD) allows triggering a multi-precision convolutional neural network (CNN) engine for subsequent face recognition (FR). The 22nm SoC can therefore dynamically trade-off image analysis depth, frames-per-second (FPS), accuracy, and power consumption. It implements complete end-to-end edge processing, enabling always-on FD and FR within the tight 1mW power budget of a 55mm diameter indoor solar panel. The SoC achieves >2x improvement in energy efficiency at iso-accuracy and iso-FPS over state-of-the-art (SoA) systems
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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
- …
