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Position-Aware k-mer Categorization for Oxford Nanopore Sequencing Reads

Tomas, Filip Šikić, Mile

2026-05-25

Recent work has shown that explicit k-mer categorization at the read level can support long-read genome assembly by distinguishing erroneous, single-copy and multi-copy, and repetitive sequence content, with copy-number-related categories reflecting …

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2026 49th MIPRO ICT and Electronics Convention (MIPRO)

2026 49th MIPRO ICT and Electronics Convention (MIPRO) 2026

DOI10.1109/mipro70003.2026.11591728

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Broadband multiwavelength properties of the archetypal blazar 3C 279 during the 2017 Event Horizon Telescope campaign

Principe, G. Babić, Ana Bošnjak, Željka Marija Dominis Prester, Dijana Hrupec, Dario Lulic, Lorena Manganaro, Marina Maruševec, Petra Strišković, Jelena Terzić, Tomislav

2026

Context. The archetypal blazar 3C 279 has a prominent relativistic jet and strong broadband variability across the electromagnetic spectrum. In April 2017, the Event Horizon Telescope (EHT) observed 3C 279 with an unprecedented angular resolution of …

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Astronomy & astrophysics Vol. 712

DOI10.1051/0004-6361/202659551 eISSN1432-0746 pISSN0004-6361

Repozitorij FER-a

galaxies: active - galaxies jets - gamma rays galaxies - quasars individual: 3C 279

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Fusion of LiDAR and AIS data for improved maritime object detection

Obradović, Juraj Možnik, Dorian Mišković, Nikola

2026

Maritime autonomous systems require robust perception to address the high rate of human-error-caused accidents in the maritime domain. We present a hybrid detection framework combining YOLO11-based neural network detection on bird's-eye-view LiDAR pr…

Centar izvrsnosti MARBLE društvo s ograničenom odgovornošću za istraživanje i razvoj

Sveučilište u Zagrebu Sveučilište u Zagrebu Fakultet elektrotehnike i računarstva Zavod za automatiku i računalno inženjerstvo

Control engineering practice Vol. 175

DOI10.1016/j.conengprac.2026.107100 eISSN1873-6939 pISSN0967-0661

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Maritime robotics Object detection Sensor fusion LiDAR perception LIDAR-AIS fusion

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Prilog u časopisu Dostupan nakon (2028-03-02)

Impedance Myography Circle Mapping: A Geometry-Based Multi-Frequency EIM Framework for Quantitative Assessment of Post-Stroke Muscle Impairment

Zhou, Junwei Xu, Peitao Xu, Pan Wang, Weihan Wei, Wei Xue, Xiehua Lučev Vasić, Željka Cifrek, Mario Liu, Yuqing Wei, De Gao, Yueming

2026

Post-stroke neuromuscular impairment arises from heterogeneous structural and electrophysiological alterations, including disrupted membrane integrity, fiber atrophy, and increased intramuscular fat. These changes substantially alter the resistive-ca…

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IEEE transactions on biomedical engineering str. 1–12

DOI10.1109/tbme.2026.3669773 eISSN1558-2531 pISSN0018-9294

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Electrical impedance myography (EIM) stroke rehabilitation impedance myography circle mapping (IMCM) spasticity machine learning bioelectrical biomarkers

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Comparative Evaluation of Embedding and Generative Model Combinations in Retrieval-Augmented Generation Pipelines

Hitl, Mateo Bagić Babac, Marina Mornar, Vedran

2026-06-23

Purpose Retrieval-augmented generation (RAG) systems integrate information retrieval with generative language models to improve the relevance, accuracy and explainability of AI-driven responses. This study evaluates how different configurations of em…

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Data Technologies and Applications Vol. Early Access, str. 1–19

DOI10.1108/DTA-07-2025-0609 pISSN0033-0337

Repozitorij FER-a

Retrieval-augmented generation Knowledge management Embeddings Large language models Information retrieval Evaluation Faithfulness Answer relevance

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Multiview Job-Resume Matching With Contrastive Learning and LLM-Based Paraphrase Augmentation

Čeović, Helena Vladimir, Klemo Delač, Goran Šilić, Marin

2026-07-02

Job-resume matching is essential for scalable recruitment, yet remains challenging due to lexical ambiguity, structural heterogeneity, and limited labeled data. We propose a dual-encoder framework trained with multiview contrastive learning and enhan…

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IEEE access Vol. 14, str. 106601–106614

DOI10.1109/access.2026.3709651 eISSN2169-3536

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contrastive learning dual encoders information retrieval job-resume matching multiview learning paraphrase augmentation

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Co-Simulation-Based Evaluation of Control Mechanisms for Active Low-Voltage Network Scheduling

Dubravac, Marina Topic, Danijel Knezevic, Goran Antic, Tomislav

2026

Sveučilište Josipa Jurja Strossmayera u Osijeku Sveučilište Josipa Jurja Strossmayera u Osijeku, Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

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IEEE Access Vol. 14, str. 108985–108999

DOI10.1109/access.2026.3713666 eISSN2169-3536

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Modeling Advanced Persistent Threats Through Organizational Roles for Adversary Emulation and Cyber Threat Intelligence

Gernardt, Dalibor Groš, Stjepan Ćutić, Davor

2026

Existing research and public reports on state-sponsored or state-directed Advanced Persistent Threats (APTs) describe adversary behavior mainly through tools, tactics, techniques, and procedures, but are less explicit about how long-running operation…

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Sveučilište obrane i sigurnosti Dr. Franjo Tuđman

IEEE access Vol. 14, str. 111636–111665

DOI10.1109/ACCESS.2026.3715473 eISSN2169-3536

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Advanced persistent threat (APT) adversary emulation cyber threat intelligence organizational roles red teaming

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RetailSplats: Product Recognition in 3D Gaussian Splatting Retail Stores

Budimir, Lovre-Antonio Lončarić, Sven

2026-09-08

3D scene understanding is a fundamental computer vision problem that supports applications such as autonomous navigation, object localization, and robotic simulation and interaction across diverse environments. Retail stores, however, present a parti…

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The 19th European Conference on Computer Vision Workshops - ECCV 2026 Workshops 2026

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Product Recognition Zero-Shot Localization 3D Gaussian Splatting 3D Scene Understanding Vision-Language Models

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Beyond Natural-Image Foundation Models: Benchmarking Satellite Pretraining for Ophthalmic Image Analysis

Budimir, Lovre-Antonio Gong, Mingya Alexa Quinney, Alyssa Matovinović, Ivana Zhou, Yukun Keane, Pearse A. Lončarić, Sven Sarunic, Marinko V.

2026-09

Vision Foundation Models (VFMs) have emerged as a promising approach in medical imaging, producing broadly applicable systems that can be efficiently adapted across diverse imaging modalities, anatomical regions, and clinical tasks. However, VFMs req…

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The 19th European Conference on Computer Vision Workshops - ECCV 2026 Workshops 2026

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Vision Foundation Model Medical Foundation Model DINOv3 Ophthalmology Satellite imagery

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