Opportunistic human activity and context recognition

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Despite the significant progress in recent years, deep face recognition is often treated as a "black box" and has been criticized for lacking explainability. It becomes increasingly important to understand the characteristics and decisions of deep face rec ...

State-of-the-art face recognition systems require vast amounts of labeled training data. Given the priority of privacy in face recognition applications, the data is limited to celebrity web crawls, which have issues such as limited numbers of identities. O ...

As an 'early alerting' sense, one of the primary tasks for the human visual system is to recognize distant objects. In the specific context of facial identification, this ecologically important task has received surprisingly little attention. Most studies ...

Biological motor control is versatile, efficient, and depends on proprioceptive feedback. Muscles are flexible and undergo continuous changes, requiring distributed adaptive control mechanisms that continuously account for the body's state. The canonical r ...

This training dataset includes a total of 34,913 manually transcribed text segments. It is dedicated to the handwritten text recognition (HTR) of historical sources, typically tabular records, such as censuses. This dataset is based on a sample of 83 pages ...

In this paper we propose a novel virtual simulation-pilot engine for speeding up air traffic controller (ATCo) training by integrating different state-of-the-art artificial intelligence (AI)-based tools. The virtual simulation-pilot engine receives spoken ...

Automatic Speech Recognition (ASR), as the assistance of speech communication between pilots and air-traffic controllers, can significantly reduce the complexity of the task and increase the reliability of transmitted information. ASR application can lead ...

Occupant detection and recognition support functional goals such as security, healthcare, and energy management in buildings. Typical sensing approaches, such as smartphones and cameras, undermine the privacy of building occupants and inherently affect the ...

Face recognition has become a popular authentication tool in recent years. Modern state-of-the-art (SOTA) face recognition methods rely on deep neural networks, which extract discriminative features from face images. Although these methods have high recogn ...

Criminal investigations require manual intervention of several investigators and translators. However, the amount and the diversity of the data collected raises many challenges, and cross-border investigations against organized crime can quickly impossible ...

Voice communication is the main channel to exchange information between pilots and Air-Traffic Controllers (ATCos). Recently, several projects have explored the employment of speech recognition technology to automatically extract spoken key information suc ...

In this paper, we develop Automatic Speech Recognition (ASR) systems for multi-genre speech recognition of low-resource languages where training data is predominantly conversational speech but test data can be in one of the following genres: news broadcast ...

We propose a deep neural network based image-to-image translation for domain adaptation, which aims at finding translations between image domains. Despite recent GAN based methods showing promising results in image-to-image translation, they are prone to f ...

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of b ...

Makeup is a simple and easy instrument that can alter the appearance of a person’s face, and hence, create a presentation attack on face recognition (FR) systems. These attacks, especially the ones mimicking ageing, are difficult to detect due to their clo ...

Feature selection problems arise in a variety of applications, such as microarray analysis, clinical prediction, text categorization, image classification and face recognition, multi-label learning, and classification of internet traffic. Among the various ...

Multimedia databases are growing rapidly in size in the digital age. To increase the value of these data and to enhance the user experience, there is a need to make these videos searchable through automatic indexing. Because people appearing and talking in ...

A large part of computer vision research is devoted to building models and algorithms aimed at understanding human appearance and behaviour from images and videos. Ultimately, we want to build automated systems that are at least as capable as people when i ...

Medical Internet of Things (IoT) solutions are already paving the way towards the realization of Smart Hospitals. Following this trend, we propose an IoT cloud-based network for anesthesia on-line monitoring. This architecture allows the anesthesiologist t ...

Recent past has seen a lot of developments in the field of image-based dietary assessment. Food image classification and recognition are crucial steps for dietary assessment. In the last couple of years, advancements in the deep learning and convolutional ...

Opportunistic human activity and context recognition

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Explanation of Face Recognition via Saliency Maps

How to Boost Face Recognition with StyleGAN?

Recognizing distant faces

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Lausanne Historical Censuses Dataset HTR 35k

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

A Two-Step Approach To Leverage Contextual Data: Speech Recognition In Air-Traffic Communications

Using footstep-induced vibrations for occupant detection and recognition in buildings

On the Recognition Performance of BioHashing on state-of-the-art Face Recognition models

ROXANNE Research Platform: Automate criminal investigations

Automatic Call Sign Detection: Matching Air Surveillance Data with Air Traffic Spoken Communications

Multitask adaptation with Lattice-Free MMI for multi-genre speech recognition of low resource languages

ExprADA: Adversarial domain adaptation for facial expression analysis

Behavioural compass: animal behaviour recognition using magnetometers

Detection of Age-Induced Makeup Attacks on Face Recognition Systems Using Multi-Layer Deep Features

Theoretical foundations of forward feature selection methods based on mutual information

Multimodal person recognition in audio-visual streams

Variational Methods for Human Modeling

Live Demonstration: An IoT Cloud-Based Architecture for Anesthesia Monitoring

Food/Non-food Image Classification and Food Categorization using Pre-Trained GoogLeNet Model