Abstract: Dynamic convolution demonstrates outstanding representation capabilities, which are crucial for natural image segmentation. However, it fails when applied to medical image segmentation (MIS) ...

It’s not a secret that today’s enterprise networks have grown increasingly complex. Workloads, users, and applications now span legacy on-premises and brand new AI data centers, cloud environments, ...

Imagine this: your smart home devices, guest Wi-Fi, and workstations all coexist on the same network. A single compromised IoT device could expose sensitive data or disrupt your entire system. It’s a ...

Abstract: The 3-D point cloud semantic segmentation extends the development of computer vision. Accurate point cloud semantic segmentation is a fundamental problem in point cloud applications. However ...

Chief Product Officer; Co-President Global Educ. As CTO of an international fintech and an advisory board member to the Payment Card Industry Security Standards Council, I often spend my free time ...

End-of-life devices remain a pervasive security concern in the enterprise, as do poorly segmented networks, unpatched systems, and visibility gaps, according to recent telemetry reports. The extent to ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Leaders across government and industry are confronting a hard truth: The attack surface for critical infrastructure security has expanded as aging systems have been retrofitted with networked ...

Effective network management is critical for ensuring reliable system performance and safeguarding the flow of information that powers nearly every business operation. AI has quickly become the ...

Network segmentation has been a security best practice for decades, yet for many reasons, not all network deployments have fully embraced the approach of microsegmentation. With ransomware attacks ...