Building and roof type classification on 3D city models

Scale Learning in Scale-Equivariant Convolutional networks

Architectural Innovations for Efficient Denoising and Classification: A Manual vs. Neural Architecture Search Comparison

Particle Inspection: Modules of the Visual Particle Inspection Subsystem; Detection of Particle Contamination in Medicine Containers with Novel Solutions for Background Subtraction and Segmentation, Classification, and Tracking

Real-Time Detection and Classification of Purkinje-Cell Neural Activity

Predictive Analysis of Anti-NMDA-Receptor Encephalitis: using a Random Forest Classifier on EEG Data

Classification of micro-Doppler signatures with the use of orthogonal moment-based features

Automatic text-based speech overlap classification: A novel approach using Large Language Models

Self-supervised Learning for Tumor Microenvironment Analysis: Addressing Label Scarcity in Multiplexed Immunofluorescence Imaging with Novel Feature Extraction Techniques

Digging through the dirt: a general method for abstract discrete state estimation with limited prior knowledge

Airborne LiDAR data tree cover map: LiDAR data as additional data to Sentinel-2 spectral images to enhance land cover classification

Global identification and characterization of drivers of shoreline evolution: A novel method using Satellite Derived Shorelines and spatiotemporal characteristics

Interpretation of the Machine Learning Fault Classification Model Results Using Explainable Features

Handball throw type detection and classification with different machine learning models based on wrist IMU data during a handball practice

Detecting plume-driven polynyas from dual-pol SAR imagery

A Machine Learning approach for 3D load feasibility prediction

Automatic Detection of Mind Wandering Based on Eye Movement from the Mementos Data Set

Using pre-trained convolutional neural networks to predict maturity levels of strawberries

Vegetation monitoring in coastal areas using readily available Remote Sensing data

The impact of spatial resolution and satellite data type characteristics on Automated Damage Assessment using a Convolutional Neural Network