From the 1 of 8 linked papers with an AI index.
8 papers
Watershed vs. Region Growing for Individual Tree Segmentation from Airborne LiDAR: An Urban Case Study in Bologna
Aldo Canfora, Tommaso Rondini, Matteo Falcioni +1
The paper compares two LiDAR-based methods—watershed segmentation on a canopy height model and point-wise region growing—to identify individual urban trees in Bologna and derives b…
Calibrating the Instrument: Controllability of an LLM-Driven Synthetic Population
Mirko Degli Esposti
Generative Synthetic Populations (GSP) -- the convergence of population synthesis, agent-based modelling, and LLM agents -- are attracting growing interest for urban simulation and…
Scalable Maximum Entropy Population Synthesis via Persistent Contrastive Divergence
Mirko Degli Esposti
Maximum entropy (MaxEnt) modelling provides a principled framework for generating synthetic populations from aggregate census data, without access to individual-level microdata. Th…
A Zipf-preserving, long-range correlated surrogate for written language and other symbolic sequences
Marcelo A. Montemurro, Mirko Degli Esposti
Symbolic sequences such as written language and genomic DNA display characteristic frequency distributions and long-range correlations extending over many symbols. In language, thi…
Trailer Reimagined: An Innovative, Llm-DRiven, Expressive Automated Movie Summary framework (TRAILDREAMS)
Roberto Balestri, Pasquale Cascarano, Mirko Degli Esposti +1
This paper introduces TRAILDREAMS, a framework that uses a large language model (LLM) to automate the production of movie trailers. The purpose of LLM is to select key visual seque…
An Automatic Deep Learning Approach for Trailer Generation through Large Language Models
Roberto Balestri, Pasquale Cascarano, Mirko Degli Esposti +1
Trailers are short promotional videos designed to provide audiences with a glimpse of a movie. The process of creating a trailer typically involves selecting key scenes, dialogues…