Papers Deep Learning
“Deep Learning” 태그가 달린 논문 9,423편 · 필터 해제
Integrating Radiomics with Deep Learning Enhances Multiple Sclerosis Lesion Delineation
Background: Accurate lesion segmentation is critical for multiple sclerosis (MS) diagnosis, yet current deep learning approaches face robustness challenges. Aim: This study improves MS lesion segmentation by combining da…
Deep LearningLesion SegmentationSegmentationObject-Centric Neuro-Argumentative Learning
Over the last decade, as we rely more on deep learning technologies to make critical decisions, concerns regarding their safety, reliability and interpretability have emerged. We introduce a novel Neural Argumentative Le…
Deep LearningObjectDeep Learning Surrogates for Real-Time Gas Emission Inversion
Real-time identification and quantification of greenhouse-gas emissions under transient atmospheric conditions is a critical challenge in environmental monitoring. We introduce a spatio-temporal inversion framework that …
Bayesian InferenceDeep LearningAdaptive Action Duration with Contextual Bandits for Deep Reinforcement Learning in Dynamic Environments
Deep Reinforcement Learning (DRL) has achieved remarkable success in complex sequential decision-making tasks, such as playing Atari 2600 games and mastering board games. A critical yet underexplored aspect of DRL is the…
Atari GamesBoard GamesComputational EfficiencyDecision Making+6PeakWeather: MeteoSwiss Weather Station Measurements for Spatiotemporal Deep Learning
Accurate weather forecasts are essential for supporting a wide range of activities and decision-making processes, as well as mitigating the impacts of adverse weather events. While traditional numerical weather predictio…
Deep LearningGraph structure learningImputationTime Series ForecastingProjecting U.S. coastal storm surge risks and impacts with deep learning
Storm surge is one of the deadliest hazards posed by tropical cyclones (TCs), yet assessing its current and future risk is difficult due to the phenomenon's rarity and physical complexity. Recent advances in artificial i…
Deep LearningForecast-Then-Optimize Deep Learning Methods
Time series forecasting underpins vital decision-making across various sectors, yet raw predictions from sophisticated models often harbor systematic errors and biases. We examine the Forecast-Then-Optimize (FTO) framewo…
Decision MakingDeep LearningManagementTime Series ForecastingDeep Learning-Based Multi-Object Tracking: A Comprehensive Survey from Foundations to State-of-the-Art
Multi-object tracking (MOT) is a core task in computer vision that involves detecting objects in video frames and associating them across time. The rise of deep learning has significantly advanced MOT, particularly withi…
Deep LearningMulti-Object TrackingObject TrackingA Comprehensive Survey on Deep Learning Solutions for 3D Flood Mapping
Flooding remains a major global challenge, worsened by climate change and urbanization, demanding advanced solutions for effective disaster management. While traditional 2D flood mapping techniques provide limited insigh…
Computational EfficiencyDeep LearningManagementSurveyA large-scale, physically-based synthetic dataset for satellite pose estimation
The Deep Learning Visual Space Simulation System (DLVS3) introduces a novel synthetic dataset generator and a simulation pipeline specifically designed for training and testing satellite pose estimation solutions. This w…
BenchmarkingDataset GenerationDeep LearningPose Estimation+1Evaluating Sensitivity Parameters in Smartphone-Based Gaze Estimation: A Comparative Study of Appearance-Based and Infrared Eye Trackers
This study evaluates a smartphone-based, deep-learning eye-tracking algorithm by comparing its performance against a commercial infrared-based eye tracker, the Tobii Pro Nano. The aim is to investigate the feasibility of…
Deep LearningGaze EstimationSensitivityDeep Learning-based mmWave MIMO Channel Estimation using sub-6 GHz Channel Information: CNN and UNet Approaches
Future wireless multiple-input multiple-output (MIMO) systems will integrate both sub-6 GHz and millimeter wave (mmWave) frequency bands to meet the growing demands for high data rates. MIMO link establishment typically …
Deep LearningEfficiency Robustness of Dynamic Deep Learning Systems
Deep Learning Systems (DLSs) are increasingly deployed in real-time applications, including those in resourceconstrained environments such as mobile and IoT devices. To address efficiency challenges, Dynamic Deep Learnin…
Deep LearningEnergy-Efficient Deep Learning for Traffic Classification on Microcontrollers
In this paper, we present a practical deep learning (DL) approach for energy-efficient traffic classification (TC) on resource-limited microcontrollers, which are widely used in IoT-based smart systems and communication …
Computational EfficiencyDeep LearningHardware Aware Neural Architecture SearchNeural Architecture Search+1Empirical Quantification of Spurious Correlations in Malware Detection
End-to-end deep learning exhibits unmatched performance for detecting malware, but such an achievement is reached by exploiting spurious correlations -- features with high relevance at inference time, but known to be use…
Deep LearningMalware DetectionSpatiotemporal deep learning models for detection of rapid intensification in cyclones
Cyclone rapid intensification is the rapid increase in cyclone wind intensity, exceeding a threshold of 30 knots, within 24 hours. Rapid intensification is considered an extreme event during a cyclone, and its occurrence…
Data AugmentationDeep LearningEnsemble LearningSynthetic Data GenerationCALT: A Library for Computer Algebra with Transformer
Recent advances in artificial intelligence have demonstrated the learnability of symbolic computation through end-to-end deep learning. Given a sufficient number of examples of symbolic expressions before and after the t…
Deep LearningData-Efficient Challenges in Visual Inductive Priors: A Retrospective
Deep Learning requires large amounts of data to train models that work well. In data-deficient settings, performance can be degraded. We investigate which Deep Learning methods benefit training models in a data-deficient…
Data AugmentationDeep LearningTransfer LearningCanadaFireSat: Toward high-resolution wildfire forecasting with multiple modalities
Canada experienced in 2023 one of the most severe wildfire seasons in recent history, causing damage across ecosystems, destroying communities, and emitting large quantities of CO2. This extreme wildfire season is sympto…
Deep LearningEarth ObservationBiologically Inspired Deep Learning Approaches for Fetal Ultrasound Image Classification
Accurate classification of second-trimester fetal ultrasound images remains challenging due to low image quality, high intra-class variability, and significant class imbalance. In this work, we introduce a simple yet pow…
AnatomyDeep Learningimage-classificationImage Classification