output
20132026
most citedA Hybrid Solution Method for the Capacitated Vehicle Routing Problem Using a Quantum Annealer

191 citations

70 papers

cs.AR2026★ 1 cited

Energy-Efficient CNN Acceleration with MSDF Digit-Serial Arithmetic on FPGA

Muhammad Usman, Yousef Sadegheih, Dorit Merhof

This paper presents an energy-efficient hardware acceleration of the convolutional layers in the U-Net architecture for image segmentation, implemented on FPGA. While digit-serial…

cs.CV2026★ 1 cited

SiMiC: Context-Aware Silicon Microstructure Characterization Using Attention-Based Convolutional Neural Networks for Field-Emission Tip Analysis

Jing Jie Tan, Rupert Schreiner, Matthias Hausladen +8

Accurate characterization of silicon microstructures is essential for advancing microscale fabrication, quality control, and device performance. Traditional analysis using Scanning…

cs.CV2025★ 4 cited

The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning

Akis Linardos, Sarthak Pati, Ujjwal Baid +25

We present the design and results of the MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024, which focuses on federated learning (FL) for glioma sub-region segmentation in m…

cs.CV2025★ 6 cited

Med-VCD: Mitigating Hallucination for Medical Large Vision Language Models through Visual Contrastive Decoding

Zahra Mahdavi, Zahra Khodakaramimaghsoud, Hooman Khaloo +4

Large vision-language models (LVLMs) are now central to healthcare applications such as medical visual question answering and imaging report generation. Yet, these models remain vu…

quant-ph2025

Towards Quantum Software for Quantum Simulation

Maja Franz, Lukas Schmidbauer, Joshua Ammermann +2

Quantum simulation is a leading candidate for demonstrating practical quantum advantage over classical computation, as it is believed to provide exponentially more compute power th…

cs.CV2025

Learning Neural Parametric 3D Breast Shape Models for Metrical Surface Reconstruction From Monocular RGB Videos

Maximilian Weiherer, Antonia von Riedheim, Vanessa Brébant +2

We present a neural parametric 3D breast shape model and, based on this model, introduce a low-cost and accessible 3D surface reconstruction pipeline capable of recovering accurate…