A Two-Layered Anomaly Detection Technique Based on Multi-modal Flow Behavior Models

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Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

MapPool is a dataset of 75 million potential maps and textual captions. It has been derived from CommonPool, a dataset consisting of 12 billion text-image pairs from the Internet. The images have been encoded by a vision transformer and classified into map ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

We propose a novel system leveraging deep learning-based methods to predict urban traffic accidents and estimate their severity. The major challenge is the data imbalance problem in traffic accident prediction. The problem is caused by numerous zero values ...

The usage of Unmanned Aerial Systems (UAS) in traffic monitoring has advantages such as broader vision, flexibility, privacy, and cost-efficiency compared to other traffic monitoring sensors like loop detectors or fixed surveillance cameras. UAS has been i ...

Ridesourcing has driven a lot of attention in recent years with the expansion of companies like Uber, Lift, and many others around the world. Companies use mobile applications connected through the internet to match drivers and their passengers real-time. ...

Microscopic traffic flow models can be distinguished in lane-based or lane-free depending on the degree of lane-discipline. This distinction holds true only if motorcycles are neglected in lane-based traffic. In cities, as opposed to highways, this is an o ...

In-network devices around the world monitor and tamper with connections for many reasons, including intrusion prevention, combating spam or phishing, and country-level censorship. Connection tampering seeks to block access to specific domain names or keywo ...

Time-sensitive networks, as in the context of IEEE Time-Sensitive Networking (TSN) and IETF Deterministic Networking (DetNet), offer deterministic services with guaranteed bounded latency in order to support safety-critical applications. In this thesis, we ...

We investigate methods for manipulating classifier explanations while keeping the predictions unchanged. Our focus is on using a sparse attack, which seeks to alter only a minimal number of input features. We present an efficient and novel algorithm for co ...

This dissertation introduces traffic forecasting methods for different network configurations and data availability. Chapter 2 focuses on single freeway cases. Although its topology is simple, the non-linearity of traffic features makes this prediction sti ...

In this dissertation, we propose multiple methods to improve transfer learning for pretrained language models (PLMs). Broadly, transfer learning is a powerful technique in natural language processing, where a language model is first pre-trained on a data-r ...

Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...

Residential ventilative cooling via natural ventilation is influenced by outdoor air pollution. However, relative to climate, outdoor air pollution is not comprehensively considered in determining the ventilative cooling potential of buildings. To assess t ...

Decentralized signal control of congested traffic networks based on the Max-Pressure (MP) controller is theoretically proven to maximize throughput, stabilize the system and balance queues for single intersections under specific conditions. However, its pe ...

Blood pressure (BP) is a crucial indicator of cardiovascular health. Hypertension is a common life-threatening condition and a key factor of cardiovascular diseases (CVDs). Identifying abnormal BP fluctuations can allow for early detection and management o ...

Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier f ...

The safety of existing bridges may be assessed using data from monitoring. The fatigue damage induced during observation period is extrapolated to the total service duration of a structure, and the reserve capacity is estimated. However, due to the randomn ...

This research is the result of four years of practical and scientific investigation of the phenomenon of traffic evaporation, which was considered and then demonstrated to be the opposite of traffic induction. It has anchored, in practice and in time, an o ...

A Two-Layered Anomaly Detection Technique Based on Multi-modal Flow Behavior Models

Chattez avec Graph Search

Social-Transmotion: Promptable Human Trajectory Prediction

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

MapPool -Bubbling up an extremely large corpus of maps for AI

Robust machine learning for neuroscientific inference

From Prediction to Prevention: Leveraging Deep Learning in Traffic Accident Prediction Systems

Visual extensions and anomaly detection in the pNEUMA experiment with a swarm of drones

Modeling and Optimization of Ridesplitting Operations

A hybrid microscopic model for multimodal traffic with empirical observations from aerial footage

Global, Passive Detection of Connection Tampering

Worst-Case Delay Analysis of Time-Sensitive Networks with Network Calculus

Sparse Attacks for Manipulating Explanations in Deep Neural Network Models

Multivariate time series forecasting for freeway networks

Improving Generalization of Pretrained Language Models

Large-scale traffic signal control and multimodal network design

Influence of outdoor air pollution on European residential ventilative cooling potential

Critical node selection method for efficient Max-Pressure traffic signal control in large-scale congested networks

Data-driven approaches for non-invasive cuffless blood pressure monitoring

Robust Outlier Rejection for 3D Registration with Variational Bayes

Quantification of influence of monitoring duration on measured traffic action effects on fatigue of RC deck slabs of road bridges

L'évaporation du trafic, opportunités et défis pour la mobilité d'aujourd'hui et demain