Face (sociological concept) ≈ Face (sociological concept)
View article: MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Open
We present a class of efficient models called MobileNets for mobile and embedded vision applications. MobileNets are based on a streamlined architecture that uses depth-wise separable convolutions to build light weight deep neural networks…
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Online Learning: A Panacea in the Time of COVID-19 Crisis Open
Educational institutions (schools, colleges, and universities) in India are currently based only on traditional methods of learning, that is, they follow the traditional set up of face-to-face lectures in a classroom. Although many academi…
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Towards a theory of ecosystems Open
Research Summary: The recent surge of interest in “ecosystems” in strategy research and practice has mainly focused on what ecosystems are and how they operate. We complement this literature by considering when and why ecosystems emerge, a…
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A Literature Review on Impact of COVID-19 Pandemic on Teaching and Learning Open
The COVID-19 pandemic has created the largest disruption of education systems in human history, affecting nearly 1.6 billion learners in more than 200 countries. Closures of schools, institutions and other learning spaces have impacted mor…
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Online learning amid the COVID-19 pandemic: Students perspectives Open
This research study examines the attitudes of Pakistani higher education students towards compulsory digital and distance learning university courses amid Coronavirus (COVID-19). Undergraduate and postgraduate were surveyed to find their p…
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Understanding and Tackling Societal Grand Challenges through Management Research Open
“Grand challenges” are formulations of global problems that can be plausibly addressed through coordinated and collaborative effort. In this Special Research Forum, we showcase management research that examines societal problems that indiv…
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Machine Learning: An Applied Econometric Approach Open
Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. This similarity to…
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The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English Open
The RAVDESS is a validated multimodal database of emotional speech and song. The database is gender balanced consisting of 24 professional actors, vocalizing lexically-matched statements in a neutral North American accent. Speech includes …
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Online and Remote Learning in Higher Education Institutes: A Necessity in light of COVID-19 Pandemic Open
In light of the rising concerns about the spread of COVID-19 and calls to contain the Corona Virus, a growing number of tertiary institutions have shut down in regards to face-to-face classes globally. The Corona virus has revealed emergin…
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Conditional Image Generation with PixelCNN Decoders Open
This work explores conditional image generation with a new image density model based on the PixelCNN architecture. The model can be conditioned on any vector, including descriptive labels or tags, or latent embeddings created by other netw…
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Emotional Expressions Reconsidered: Challenges to Inferring Emotion From Human Facial Movements Open
It is commonly assumed that a person’s emotional state can be readily inferred from his or her facial movements, typically called emotional expressions or facial expressions . This assumption influences legal judgments, policy decisions, n…
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MesoNet: a Compact Facial Video Forgery Detection Network Open
This paper presents a method to automatically and efficiently detect face\ntampering in videos, and particularly focuses on two recent techniques used to\ngenerate hyper-realistic forged videos: Deepfake and Face2Face. Traditional\nimage f…
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Jointly Embedding Multiple Single-Cell Omics Measurements Open
Many single-cell sequencing technologies are now available, but it is still difficult to apply multiple sequencing technologies to the same single cell. In this paper, we propose an unsupervised manifold alignment algorithm, MMD-MA, for in…
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An evidence review of face masks against COVID-19 Open
The science around the use of masks by the public to impede COVID-19 transmission is advancing rapidly. In this narrative review, we develop an analytical framework to examine mask usage, synthesizing the relevant literature to inform mult…
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Roadmap on structured light Open
This article was published as Sec.5 of the "Roadmap on Structured Light" in\nJournal of Optics 19 (2017) 013001. Section 5 describes the essential elements\nof the classical theory of electromagnetic angular momentum.\n
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Internet-based vs. face-to-face cognitive behavior therapy for psychiatric and somatic disorders: an updated systematic review and meta-analysis Open
During the last two decades, Internet-delivered cognitive behavior therapy (ICBT) has been tested in hundreds of randomized controlled trials, often with promising results. However, the control groups were often waitlisted, care-as-usual o…
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InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Open
This paper describes InfoGAN, an information-theoretic extension to the Generative Adversarial Network that is able to learn disentangled representations in a completely unsupervised manner. InfoGAN is a generative adversarial network that…
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Carbon Taxes, Path Dependency, and Directed Technical Change: Evidence from the Auto Industry Open
Can directed technical change be used to combat climate change? We construct new firm-level panel data on auto industry innovation distinguishing between "dirty" (internal combustion engine) and "clean" (e.g. electric and hybrid) patents a…
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Going deeper in facial expression recognition using deep neural networks Open
Automated Facial Expression Recognition (FER) has remained a challenging and\ninteresting problem. Despite efforts made in developing various methods for\nFER, existing approaches traditionally lack generalizability when applied to\nunseen…
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Startups in times of crisis – A rapid response to the COVID-19 pandemic Open
RESEARCH SUMMARY: The discovery of the coronavirus (SARS-CoV-2) and the spread of COVID-19 have led many governments to take drastic measures. The lockdown of large parts of society and economic life has come as an exogenous shock to many …
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Options for Formulating a Digital Transformation Strategy Open
CIOs and other senior executives face the challenge of how to handle the opportunities and risks of digital transformation. To help managers address this challenge more systematically, we describe how three German media companies successfu…
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A Neural Algorithm of Artistic Style Open
In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image. Thus far the algorithmic basis of this process is unknown…
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Proceedings of the 29th ACM International Conference on Multimedia Open
Recently deep neural networks (DNNs) have achieved significant success in\nreal-world image super-resolution (SR). However, adversarial image samples with\nquasi-imperceptible noises could threaten deep learning SR models. In this\npaper, …
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Machine Learning: New Ideas and Tools in Environmental Science and Engineering Open
The rapid increase in both the quantity and complexity of data that are being generated daily in the field of environmental science and engineering (ESE) demands accompanied advancement in data analytics. Advanced data analysis approaches,…
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Resilience (Republished) Open
Resilience thinking in relation to the environment has emerged as a lens of inquiry that serves a platform for interdisciplinary dialogue and collaboration. Resilience is about cultivating the capacity to sustain development in the face of…
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Digital transformation in business and management research: An overview of the current status quo Open
It is no surprise that research on digital transformation (DT) has raised vast interest among academics in recent decades. Countries, cities, industries, companies, and people all face the same challenge of adapting to a digital world. The…
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Data Augmentation Generative Adversarial Networks Open
Effective training of neural networks requires much data. In the low-data regime, parameters are underdetermined, and learnt networks generalise poorly. Data Augmentation alleviates this by using existing data more effectively. However sta…
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Conditional Image Generation with PixelCNN Decoders Open
This work explores conditional image generation with a new image density model based on the PixelCNN architecture. The model can be conditioned on any vector, including descriptive labels or tags, or latent embeddings created by other netw…
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Qualitative Data Collection in an Era of Social Distancing Open
Qualitative researchers face unique opportunities and challenges as a result of the disruption of COVID-19. Although the pandemic represents a unique opportunity to study the crisis itself, social distancing mandates are restricting tradit…
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Teleworking in the Context of the Covid-19 Crisis Open
This article aims to analyze the implementation of teleworking as a security practice to face the crisis resulting from the Covid-19 disease. The present paper provides both theoretical and practical results. From a theoretical standpoint,…