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pro vyhledávání: '"Jeong, Sungheon"'
Autor:
Najafi, Deniz, Barkam, Hamza Errahmouni, Morsali, Mehrdad, Jeong, SungHeon, Das, Tamoghno, Roohi, Arman, Nikdast, Mahdi, Imani, Mohsen, Angizi, Shaahin
Neuro-symbolic Artificial Intelligence (AI) models, blending neural networks with symbolic AI, have facilitated transparent reasoning and context understanding without the need for explicit rule-based programming. However, implementing such models in
Externí odkaz:
http://arxiv.org/abs/2412.10187
Autor:
Jeong, Sungheon, Chen, Hanning, Yun, Sanggeon, Cho, Suhyeon, Huang, Wenjun, Liu, Xiangjian, Imani, Mohsen
This paper introduces a powerful encoder that transfers CLIP`s capabilities to event-based data, enhancing its utility and expanding its applicability across diverse domains. While large-scale datasets have significantly advanced image-based models,
Externí odkaz:
http://arxiv.org/abs/2412.03093
Autor:
Jeong, SungHeon, Barkam, Hamza Errahmouni, Yun, Sanggeon, Kim, Yeseong, Angizi, Shaahin, Imani, Mohsen
Hyperdimensional computing (HDC) enables efficient data encoding and processing in high-dimensional space, benefiting machine learning and data analysis. However, underutilization of these spaces can lead to overfitting and reduced model reliability,
Externí odkaz:
http://arxiv.org/abs/2411.14612
Autor:
Chen, Hanning, Ni, Yang, Huang, Wenjun, Liu, Yezi, Jeong, SungHeon, Wen, Fei, Bastian, Nathaniel, Latapie, Hugo, Imani, Mohsen
Vision Transformers (ViTs) have emerged as the backbone of many segmentation models, consistently achieving state-of-the-art (SOTA) performance. However, their success comes at a significant computational cost. Image token pruning is one of the most
Externí odkaz:
http://arxiv.org/abs/2409.08464
Autor:
Huang, Wenjun, Ni, Yang, Rezvani, Arghavan, Jeong, SungHeon, Chen, Hanning, Liu, Yezi, Wen, Fei, Imani, Mohsen
Human pose estimation (HPE) is crucial for various applications. However, deploying HPE algorithms in surveillance contexts raises significant privacy concerns due to the potential leakage of sensitive personal information (SPI) such as facial featur
Externí odkaz:
http://arxiv.org/abs/2409.02715
Customizable image retrieval from large datasets remains a critical challenge, particularly when preserving spatial relationships within images. Traditional hashing methods, primarily based on deep learning, often fail to capture spatial information
Externí odkaz:
http://arxiv.org/abs/2404.11025
Autor:
Huang, Wenjun, Rezvani, Arghavan, Chen, Hanning, Ni, Yang, Yun, Sanggeon, Jeong, Sungheon, Imani, Mohsen
Applications in the Internet of Things (IoT) utilize machine learning to analyze sensor-generated data. However, a major challenge lies in the lack of targeted intelligence in current sensing systems, leading to vast data generation and increased com
Externí odkaz:
http://arxiv.org/abs/2402.02043
Autor:
Huang, Wenjun, Rezvani, Arghavan, Chen, Hanning, Ni, Yang, Yun, Sanggeon, Jeong, Sungheon, Zhang, Guangyi, Imani, Mohsen
Publikováno v:
IEEE Sensors Journal; November 2024, Vol. 24 Issue: 21 p35858-35871, 14p
Akademický článek
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