5 papers
Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types
MichaÅ Romaszewski, Kamil Drejer, Katarzyna KoÅodziej +8
Sentinel-2 imagery offers open access, global coverage, and frequent revisit times, making it attractive for practical building mapping at scale; however, its native 10m resolution…
Enabling Cloud-Level Accuracy in Edge AI through IoT Data Preprocessing
Aygün Varol, Katarzyna KoÅodziej, Åukasz Sobczak +5
Large language models (LLMs) offer a natural-language interface for interpreting Internet of Things (IoT) sensor data in smart environments; however, cloud deployment introduces la…
From Articles to Canopies: Knowledge-Driven Pseudo-Labelling for Tree Species Classification using LLM Experts
MichaÅ Romaszewski, Dominik KopeÄ, MichaÅ Cholewa +6
Hyperspectral tree species classification is challenging due to limited and imbalanced class labels, spectral mixing (overlapping light signatures from multiple species), and ecolo…
Semantic Depth Matters: Explaining Errors of Deep Vision Networks through Perceived Class Similarities
Katarzyna Filus, MichaŠRomaszewski, Mateusz Żarski
Understanding deep neural network (DNN) behavior requires more than evaluating classification accuracy alone; analyzing errors and their predictability is equally crucial. Current…
Quantum-aware Transformer model for state classification
PrzemysÅaw SekuÅa, Przemysław Sekuła, Michał Romaszewski +7
Entanglement is a fundamental feature of quantum mechanics, playing a crucial role in quantum information processing. However, classifying entangled states, particularly in the mix…