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pro vyhledávání: '"JOSHI, AMIT"'
Network intrusion detection is critical for securing modern networks, yet the complexity of network traffic poses significant challenges to traditional methods. This study proposes a Temporal Convolutional Network(TCN) model featuring a residual bloc
Externí odkaz:
http://arxiv.org/abs/2412.17452
The rapid advancement in Large Language Models has been met with significant challenges in their training processes, primarily due to their considerable computational and memory demands. This research examines parallelization techniques developed to
Externí odkaz:
http://arxiv.org/abs/2405.15628
Autor:
Bakliwal, Aagam, Joshi, Amit D.
In the dynamic realm of deepfake detection, this work presents an innovative approach to validate video content. The methodology blends advanced 2-dimensional and 3-dimensional Convolutional Neural Networks. The 3D model is uniquely tailored to captu
Externí odkaz:
http://arxiv.org/abs/2310.16388
The conventional method of glucose measurement such as pricking blood from the body is prevalent which brings pain and trauma. Invasive methods of measurement sometimes raise the risk of blood infection to the patient. Sometimes, some of the physiolo
Externí odkaz:
http://arxiv.org/abs/2308.11952