Related papers: Stop the Open Data Bus, We Want to Get Off
DNA sequencing is becoming increasingly commonplace, both in medical and direct-to-consumer settings. To promote discovery, collected genomic data is often de-identified and shared, either in public repositories, such as OpenSNP, or with…
Operational urban transport models require to gather heterogeneous sets of data and often integrate different sub-models. Their systematic validation and reproducible application therefore remains problematic. We propose in this…
Person re-identification (re-ID) plays an important role in applications such as public security and video surveillance. Recently, learning from synthetic data, which benefits from the popularity of synthetic data engine, have achieved…
This paper presents an approach to tackle the re-identification problem. This is a challenging problem due to the large variation of pose, illumination or camera view. More and more datasets are available to train machine learning models…
The increasing capabilities of deep neural networks for re-identification, combined with the rise in public surveillance in recent years, pose a substantial threat to individual privacy. Event cameras were initially considered as a…
Ensuring travelers' safety on roads has become a research challenge in recent years. We introduce a novel safe route planning problem and develop an efficient solution to ensure the travelers' safety on roads. Though few research attempts…
This workshop invites researchers and practitioners to participate in exploring behavioral change support intelligent transportation applications. We welcome submissions that explore intelligent transportation systems (ITS), which interact…
Public transport network constitutes for an indispensable part of a city by providing mobility services to the general masses. To improve ease of access and reduce infrastructural investments, public transport authorities often adopt proof…
The development of positioning technologies has resulted in an increasing amount of mobility data being available. While bringing a lot of convenience to people's life, such availability also raises serious concerns about privacy. In this…
Over the last decades, the world has been witnessing growing threats to the security in urban spaces, which has augmented the relevance given to visual surveillance solutions able to detect, track and identify persons of interest in crowds.…
Data security, which is concerned with the prevention of unauthorized access to computers, databases, and websites, helps protect digital privacy and ensure data integrity. It is extremely difficult, however, to make security watertight,…
In the cases when public health authorities confirm a patient with highly contagious disease, they release the summaries about patient locations and travel information. However, due to privacy concerns, these releases do not include the…
Social platforms such as Reddit have a network of communities of shared interests, with a prevalence of posts and comments from which one can infer users' Personal Information Identifiers (PIIs). While such self-disclosures can lead to…
In this paper, we describe a case study in a big metropolis, in which from data collected by digital sensors, we tried to understand mobility patterns of persons using buses and how this can generate knowledge to suggest interventions that…
Secondary use of data already collected in clinical studies has become more and more popular in recent years, with the commitment of the pharmaceutical industry and many academic institutions in Europe and the US to provide access to their…
What kind of questions about human mobility can computational analysis help answer? How to translate the findings into anthropology? We analyzed a publicly available data set of road traffic counters in Slovenia to answer these questions.…
This position statement is a response to the Office of Science and Technology Policy's Request for Information on "Equitable Data Engagement and Accountability." This response considers data equity specifically for people with disabilities.…
Limiting online data collection to the minimum required for specific purposes is mandated by modern privacy legislation such as the General Data Protection Regulation (GDPR) and the California Consumer Protection Act. This is particularly…
Deep learning technology promotes the rapid development of person re-identifica-tion (re-ID). However, some challenges are still existing in the open-world. First, the existing re-ID research usually assumes only one factor variable (view,…
The Internet traffic data produced by the Internet of Things (IoT) devices are collected by Internet Service Providers (ISPs) and device manufacturers, and often shared with their third parties to maintain and enhance user services.…