output
20082026
most citedMachine Learning based System for Vessel Turnaround Time Prediction

30 citations

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6 papers · 1 filter

cs.CV2026

ENEAS: Embedding-guided Neural Ensemble for Adaptive Segmentation

Javier del Pino, Salvador Rodríguez, Alejandro Garabito +2

We present ENEAS, a unified, text-promptable method for instance tracking and semantic discovery. Text-promptable segmentation models, including the latest foundation models such a…

cs.CV2024★ 1 cited

[Citation needed] Data usage and citation practices in medical imaging conferences

Théo Sourget, Ahmet Akkoç, Stinna Winther +5

Medical imaging papers often focus on methodology, but the quality of the algorithms and the validity of the conclusions are highly dependent on the datasets used. As creating data…

cs.CV2021★ 22 cited

Automated System for Ship Detection from Medium Resolution Satellite Optical Imagery

Dejan Stepec, Tomaz Martincic, Danijel Skocaj

In this paper, we present a ship detection pipeline for low-cost medium resolution satellite optical imagery obtained from ESA Sentinel-2 and Planet Labs Dove constellations. This…

cs.CV2019★ 18 cited

Influence of segmentation on deep iris recognition performance

Juš Lozej, Dejan Štepec, Vitomir Štruc +1

Despite the rise of deep learning in numerous areas of computer vision and image processing, iris recognition has not benefited considerably from these trends so far. Most of the e…

cs.CV2018★ 19 cited

Effective Use of Synthetic Data for Urban Scene Semantic Segmentation

Fatemeh Sadat Saleh, Mohammad Sadegh Aliakbarian, Mathieu Salzmann +2

Training a deep network to perform semantic segmentation requires large amounts of labeled data. To alleviate the manual effort of annotating real images, researchers have investig…

cs.CV2013

A Face-like Structure Detection on Planet and Satellite Surfaces using Image Processing

Kazutaka Kurihara, Masakazu Takasu, Kazuhiro Sasao +5

This paper demonstrates that face-like structures are everywhere, and can be de-tected automatically even with computers. Huge amount of satellite images of the Earth, the Moon, th…