Zobrazeno 1 - 9
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pro vyhledávání: '"Zolfi, Alon"'
Autor:
Ganon, Ben, Zolfi, Alon, Hofman, Omer, Singh, Inderjeet, Kojima, Hisashi, Elovici, Yuval, Shabtai, Asaf
In recent years, conversational large language models (LLMs) have shown tremendous success in tasks such as casual conversation, question answering, and personalized dialogue, making significant advancements in domains like virtual assistance, social
Externí odkaz:
http://arxiv.org/abs/2411.19038
Vision transformers have contributed greatly to advancements in the computer vision domain, demonstrating state-of-the-art performance in diverse tasks (e.g., image classification, object detection). However, their high computational requirements gro
Externí odkaz:
http://arxiv.org/abs/2402.02554
In recent years, there has been a significant trend in deep neural networks (DNNs), particularly transformer-based models, of developing ever-larger and more capable models. While they demonstrate state-of-the-art performance, their growing scale req
Externí odkaz:
http://arxiv.org/abs/2312.02220
Autor:
Zolfi, Alon, Amit, Guy, Baras, Amit, Koda, Satoru, Morikawa, Ikuya, Elovici, Yuval, Shabtai, Asaf
Out-of-distribution (OOD) detection has attracted a large amount of attention from the machine learning research community in recent years due to its importance in deployed systems. Most of the previous studies focused on the detection of OOD samples
Externí odkaz:
http://arxiv.org/abs/2212.02081
Adversarial attacks against deep learning-based object detectors (ODs) have been studied extensively in the past few years. These attacks cause the model to make incorrect predictions by placing a patch containing an adversarial pattern on the target
Externí odkaz:
http://arxiv.org/abs/2211.08859
Adversarial attacks against deep learning-based object detectors have been studied extensively in the past few years. Most of the attacks proposed have targeted the model's integrity (i.e., caused the model to make incorrect predictions), while adver
Externí odkaz:
http://arxiv.org/abs/2205.13618
Deep learning-based facial recognition (FR) models have demonstrated state-of-the-art performance in the past few years, even when wearing protective medical face masks became commonplace during the COVID-19 pandemic. Given the outstanding performanc
Externí odkaz:
http://arxiv.org/abs/2111.10759
Physical adversarial attacks against object detectors have seen increasing success in recent years. However, these attacks require direct access to the object of interest in order to apply a physical patch. Furthermore, to hide multiple objects, an a
Externí odkaz:
http://arxiv.org/abs/2012.12528
Autor:
Zolfi, Alon, Amit, Guy, Baras, Amit, Koda, Satoru, Morikawa, Ikuya, Elovici, Yuval, Shabtai, Asaf
Out-of-distribution (OOD) detection has attracted a large amount of attention from the machine learning research community in recent years due to its importance in deployed systems. Most of the previous studies focused on the detection of OOD samples
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b669feb849f61f4eaf38f8be1a8f2c2