On hierarchical modulation to increase flow-level capacity in OFDMA-based networks

A large deviations model for latency outage for URLLC

Optimal energy management strategies in mobile networks powered by a smart grid

Comparing resource allocation schemes in multi-homed LTE/WiFi access networks

Performance evaluation of user centric multihoming strategies in LTE/WiFi networks

URLLC and eMBB coexistence in unlicensed spectrum: a preemptive approach

Joint uplink and downlink admission control to both streaming and elastic flows in CDMA/HSDPA systems

Practical implementation of Mobile TV delivery in cooperative LTE/DVB networks

Anticipatory slice resource reservation for 5G vehicular URLLC based on radio statistics

Real options for investment decisions in mobile TV infrastructure

SooGREEN: Service-oriented optimization of Green mobile networks

A game theoretical real options framework for investment decisions in mobile TV infrastructure

Long-term revenue estimation for battery performing arbitrage and ancillary services

5G innovations for new business opportunities

Simultaneous registration, segmentation and change detection from multisensor, multitemporal satellite image pairs.

Detailed Land Cover Mapping from Multitemporal Landsat-8 Data of Different Cloud Cover

Stacked Encoder-Decoders for Accurate Semantic Segmentation of Very High Resolution Satellite Datasets

Patch-based deep learning architectures for sparse annotated very high resolution datasets

A multi-task deep learning framework coupling semantic segmentation and image reconstruction for very high resolution imagery

Deep patch-based priors under a fully convolutional encoder-decoder architecture for interstitial lung disease segmentation

Test-Time Image-to-Image Translation Ensembling Improves Out-of-Distribution Generalization in Histopathology

Diversity of approaches in artificial intelligence: an opportunity for discoveries in thoracic imaging

Integrating edge/boundary priors with classification scores for building detection in very high resolution data

Me-NDT: Neural-backed Decision Tree for visual Explainability of deep Medical models

A Deep Multi-Task Learning Framework Coupling Semantic Segmentation and Fully Convolutional LSTM Networks for Urban Change Detection

Per city-block, density estimation at build-up areas from aerial RGB imagery with deep learning

Weakly Supervised Pan-Cancer Segmentation Tool

You Don't Need Domain-Specific Data Augmentations When Scaling Self-Supervised Learning

Demystification of AI-driven medical image interpretation: past, present and future

A Novel Object-Based Deep Learning Framework for Semantic Segmentation of Very High-Resolution Remote Sensing Data: Comparison with Convolutional and Fully Convolutional Networks

Gene Expression High-Dimensional Clustering towards a Novel, Robust, Clinically Relevant and Highly Compact Cancer Signature

Simultaneous Registration and Change Detection in Multitemporal, Very High Resolution Remote Sensing Data

Multitemporal Very High Resolution From Space: Outcome of the 2016 IEEE GRSS Data Fusion Contest

Differentiable Gamma Index-Based Loss Functions: Accelerating Monte-Carlo Radiotherapy Dose Simulation

Building detection in very high resolution multispectral data with deep learning features

SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel Histopathology

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge

A Joint Spatial and Magnification Based Attention Framework for Large Scale Histopathology Classification

Gigapixel Whole-Slide Images Classification Using Locally Supervised Learning

Deep learning: definition and perspectives for thoracic imaging

Graph-Based Registration, Change Detection, and Classification in Very High Resolution Multitemporal Remote Sensing Data

Have Foundational Models Seen Satellite Images?

SparseConvMIL: Sparse Convolutional Context-Aware Multiple Instance Learning for Whole Slide Image Classification

Towards Better Certified Segmentation via Diffusion Models

Artificial intelligence in lung cancer: current applications and perspectives

Detecting urban changes with recurrent neural networks from multitemporal Sentinel-2 data

Prompt-MIL: Boosting Multi-instance Learning Schemes via Task-Specific Prompt Tuning

Artificial intelligence applications for thoracic imaging

Certification of Deep Learning Models for Medical Image Segmentation

SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology