Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers

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Cyclic peptides are attractive for drug discovery due to their excellent binding properties and the potential to cross cell membranes. However, by far not all cyclic peptides are cell permeable, and measuring or predicting their membrane permeability is no ...

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

Decentralized learning (DL) is an emerging approach that enables nodes to collaboratively train a machine learning model without sharing raw data. In many application domains, such as healthcare, this approach faces challenges due to the high level of hete ...

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 ...

Foundation models have become a powerful tool in single-cell transcriptomics, enabling broad generalization across tasks such as cell type annotation, data integration, and drug response prediction. Yet, most current models are trained predominantly on hea ...

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

We introduce BLAP, a model capable of generating high-quality captions for music. BLAP leverages a fine-tuned CLAP audio encoder and a pre-trained Flan-T5 large language model. To achieve effective cross-modal alignment between music and language, BLAP uti ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

Accurate segmentation of anatomical substructures within 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm development and evaluation. In this pape ...

Example Data for DeepReefMap This dataset contains input videos in MP4 format taken with GoPro Hero 10 Cameras in Reefs in the Red Sea to demonstrate the DeepReefMap tool, which is described in the paper "Scalable Semantic 3D Mapping of Coral Reefs with De ...

Nuclear Magnetic Resonance (NMR) chemical shifts are powerful probes of local atomic and electronic structure that can be used to resolve the structures of powdered or amorphous molecular solids. Chemical shift driven structure elucidation depends critical ...

Deep learning models (DLM) are efficient replacements for computationally intensive optimization techniques. Musculoskeletal models (MSM) typically involve resource-intensive optimization processes for determining joint and muscle forces. Consequently, DLM ...

When a plasma disrupts in a tokamak, significant heat and electromagnetic loads are deposited onto the surrounding device components. These forces scale with plasma current and magnetic field strength, making disruptions one of the key challenges for futur ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Animals exhibit remarkable locomotion skills despite significant sensorimotor delays and operating in uncertain environments. Moreover, mammals acquire these skills within minutes of birth. From the Cambrian explosion to the present day, vertebrate motor c ...

What changes with age? Results in reinforcement learning (RL) are mixed. Some studies found deteriorated RL performance in older participants compared to younger controls whereas other studies did not. Daniel et al. (J Neurosci 40(5):1084–1096, 2020. 10.15 ...

Accurate forecasting of photovoltaic (PV) power production is crucial for the integration of more renewable energy sources into the power grid. PV power production is highly intermittent, due to the stochastic cloud behaviour and cloud dynamics. Previous w ...

Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers

Chattez avec Graph Search

Bulk measurement of membrane permeability for random cyclic peptides in living cells to guide drug development

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (6/6)

Fair Decentralized Learning

Incorporating Projective Geometry into Deep Learning

Abstract IA02: Cancer-specific foundation models: Friend or foe in healthcare AI?

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

Bootstrapping Language-Audio Pre-training for Music Captioning

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear Structures

Data for Paper "Scalable Semantic 3D Mapping of Coral Reefs with Deep Learning"

A Deep Learning Model for Chemical Shieldings in Molecular Organic Solids Including Anisotropy

Glenohumeral joint force prediction with deep learning

Plasma state monitoring and disruption characterization using multimodal VAEs

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

A Bio-Inspired Learning and Control Framework for Cross-Embodiment and Cross-Task Locomotion

Intact reinforcement learning in healthy ageing

Network time series forecasting in photovoltaics power production