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ORCIDYehudit Aperstein
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2020 – today
- 2025
[j3]Lital Rokach
, Yehudit Aperstein, Ayelet Akselrod-Ballin:
Deep active learning framework for chest-abdominal CT scans segmentation. Expert Syst. Appl. 263: 125522 (2025)- [i17]Assaf Lahiany, Yehudit Aperstein:
PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization. CoRR abs/2501.02508 (2025) - [i16]Yaniv Goren, Yuval Cohen, Alexander Apartsin, Yehudit Aperstein:
Beyond Words: Interjection Classification for Improved Human-Computer Interaction. CoRR abs/2509.03181 (2025) - [i15]Dor Cohen, Inga Efrosman, Yehudit Aperstein, Alexander Apartsin:
Stitching the Story: Creating Panoramic Incident Summaries from Body-Worn Footage. CoRR abs/2509.04370 (2025) - [i14]Yogev Cohen, Dudi Ohayon, Romy Somkin, Yehudit Aperstein, Alexander Apartsin:
Code Review Without Borders: Evaluating Synthetic vs. Real Data for Review Recommendation. CoRR abs/2509.04810 (2025) - [i13]Inbal Bolshinsky, Shani Kupiec, Almog Sasson, Yehudit Aperstein, Alexander Apartsin:
Do Large Language Models Need Intent? Revisiting Response Generation Strategies for Service Assistant. CoRR abs/2509.05006 (2025) - [i12]Shay Dahary, Avi Edana, Alexander Apartsin, Yehudit Aperstein:
From Joy to Fear: A Benchmark of Emotion Estimation in Pop Song Lyrics. CoRR abs/2509.05617 (2025) - [i11]Rwad Khatib, Yehudit Aperstein:
Enhancing Classification of Streaming Data with Image Distillation. CoRR abs/2509.07049 (2025) - [i10]Yehudit Aperstein, Alon Gottlib, Gal Benita, Alexander Apartsin:
Towards Knowledge-Aware Document Systems: Modeling Semantic Coverage Relations via Answerability Detection. CoRR abs/2509.08304 (2025) - [i9]Yehudit Aperstein, Alexander Apartsin:
Boosted Training of Lightweight Early Exits for Optimizing CNN Image Classification Inference. CoRR abs/2509.08318 (2025) - [i8]Matan Cohen, Shira Shani, Eden Menahem, Yehudit Aperstein, Alexander Apartsin:
Reading Between the Lines: Classifying Resume Seniority with Large Language Models. CoRR abs/2509.09229 (2025) - [i7]Yehudit Aperstein, Amit Tzahar, Alon Gottlib, Tal Verber, Ravit Shagan Damti, Alexander Apartsin:
Multi-pathology Chest X-ray Classification with Rejection Mechanisms. CoRR abs/2509.10348 (2025) - [i6]Lihi Nofar, Tomer Portal, Aviv Elbaz, Alexander Apartsin, Yehudit Aperstein:
An Interpretable Benchmark for Clickbait Detection and Tactic Attribution. CoRR abs/2509.10937 (2025) - [i5]Dvora Goncharok, Arbel Shifman, Alexander Apartsin, Yehudit Aperstein:
When Curiosity Signals Danger: Predicting Health Crises Through Online Medication Inquiries. CoRR abs/2509.11802 (2025) - [i4]Eden Mama, Liel Sheri, Yehudit Aperstein, Alexander Apartsin:
From Fuzzy Speech to Medical Insight: Benchmarking LLMs on Noisy Patient Narratives. CoRR abs/2509.11803 (2025) - [i3]Sivan Sarafian, Yehudit Aperstein:
Improving Deep Tabular Learning. CoRR abs/2509.16354 (2025) - 2024
- [j2]Ben Pinhasov, Raz Lapid, Rony Ohayon, Moshe Sipper, Yehudit Aperstein:
XAI-Based Detection of Adversarial Attacks on Deepfake Detectors. Trans. Mach. Learn. Res. 2024 (2024) - [c2]Josef Berman, Yehudit Aperstein, Abraham Yosipof:
Elucidation of Molecular Substructures from Nuclear Magnetic Resonance Spectra Using Gradient Boosting. ICANN (10) 2024: 31-42 - [i2]Ben Pinhasov, Raz Lapid, Rony Ohayon, Moshe Sipper, Yehudit Aperstein:
XAI-Based Detection of Adversarial Attacks on Deepfake Detectors. CoRR abs/2403.02955 (2024) - 2023
- [c1]G. Eli Morey, Michael G. Kawooya, Yehudit Aperstein, Igor Makienko:
Vibration-Based Estimation of Gearbox Operating Conditions: Machine Learning Approach. ICCAD 2023: 1-6 - [i1]Ben-ya Halevy, Yehudit Aperstein, Dotan Di Castro:
Offline Skill Graph (OSG): A Framework for Learning and Planning using Offline Reinforcement Learning Skills. CoRR abs/2306.13630 (2023) - 2022
- [j1]Assaf Lahiany, Yehudit Aperstein:
PTEENet: Post-Trained Early-Exit Neural Networks Augmentation for Inference Cost Optimization. IEEE Access 10: 69680-69687 (2022)
Coauthor Index
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