Visual Scene Understanding for Transportation: From Detecting Objects To Relationships

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Facial paralysis is a highly burdening condition, resulting in a patient's inability to move his musculature on one or both sides of the mouth. The restoration of facial movement is crucial for enhancing the overall patients' quality of life. The use of DE ...

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Self-supervised learning (SSL) is a machine learning approach where the data itself provides supervision, eliminating the need for external labels. The model is forced to learn about the data's inherent structure or context by solving a pretext task. With ...

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Defending aligned Large Language Models (LLMs) against jailbreaking attacks is a challenging problem, with existing approaches requiring multiple requests or even queries to auxiliary LLMs, making them computationally heavy. Instead, we focus on detecting ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Deploying energy-efficient deep neural networks on energy-constrained edge devices is an important research topic in both machine learning and circuit design communities. Both artificial neural networks (ANNs) and spiking neural networks (SNNs) have been p ...

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Sign Language conveys information through multiple channels composed of manual (handshape, hand movement) and non-manual (facial expression, mouthing, body posture) components. Sign language assessment involves giving granular feedback to a learner, in ter ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

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Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

Video DeepFakes are fake media created with Deep Learning (DL) that manipulate a person’s expression or identity. Most current DeepFake detection methods analyze each frame independently, ignoring inconsistencies and unnatural movements between frames. Som ...

Deep neural networks (DNNs) are receiving increasing attention in wind power forecasting due to their ability to effectively capture complex patterns in wind data. However, their forecast errors are severely limited by the local optimal weight issue in opt ...

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

Modern computing has enhanced our understanding of how social interactions shape collective behaviour in animal societies. Although analytical models dominate in studying collective behaviour, this study introduces a deep learning model to assess social in ...

Visual Scene Understanding for Transportation: From Detecting Objects To Relationships

Chattez avec Graph Search

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

Interact with Earth Observation Images using AI: Transparent Methods and Evaluation for Visual Question Answering

Mspo: a Machine Learning Hyperparameter Optimization Method for Enhanced Breast Cancer Image Classification

A Closer Look at Benchmarking Self-supervised Pre-training with Image Classification

Aggregating Spatial and Photometric Context for Photometric Stereo

Single-pass Detection of Jailbreaking Input in Large Language Models

Incorporating Projective Geometry into Deep Learning

Eflop: a Sparsity-aware Metric for Evaluating Computational Cost in Spiking and Non-spiking Neural Networks

Predicting Visual Stimuli From Cortical Response Recorded With Wide-Field Imaging in a Mouse

Self-supervised and few-shot learning for robust bioaerosol monitoring

Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Enabling Uncertainty Estimation in Iterative Neural Networks

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Machine Learning for Modeling Stock Returns

Efficient Temporally-Aware DeepFake Detection using H.264 Motion Vectors

Improving the accuracy and interpretability of neural networks for wind power forecasting

Stochastic pairwise preference convergence in Bayesian agents

Probing the latent hierarchical structure of data via diffusion models

Predicting the long-term collective behaviour of fish pairs with deep learning