A vision-based molten pool dimension measurement framework using YOLOv8-based region localization and Zernike-based subpixel edge refinement
Shixiong Li, Yindi Cai, Chuanzhen Wang, Wei Chen et autres
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Measurement
Chuanzhen Wang
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6Publications signalées
0Citations signalées
1Affiliations récentes
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Parallel Computing and Optimization TechniquesAdvanced Neural Network ApplicationsCloud Computing and Resource ManagementModel Reduction and Neural NetworksMachine Learning in Materials Science
Les publications récentes
ProHiFlo: Hierarchical Flow Matching with Functional Guidance for De Novo Protein Generation
Chuanzhen Wang, Meade Cleti, Pete Jano
De novo protein generation has transformative potential in therapeutic design, enzyme engineering, and synthetic biology. While diffusion-based and flow matching approaches have achieved progress, they typically operate at single resolution and lack mechanisms for incorporating functional constraints. We introduce ProHiFlo, a hierarchical …
0 citations
arXiv (Cornell University)
Self-Evolving Distributed Memory Architecture for Scalable AI Systems
Zixuan Li, Chuanzhen Wang, Haotian Sun
Distributed AI systems face critical memory management challenges across computation, communication, and deployment layers. RRAM based in memory computing suffers from scalability limitations due to device non idealities and fixed array sizes. Decentralized AI frameworks struggle with memory efficiency across NAT constrained …
0 citations
arXiv (Cornell University)
Self-Evolving Distributed Memory Architecture for Scalable AI Systems
Zixuan Li, Chuanzhen Wang, Haotian Sun
Distributed AI systems face critical memory management challenges across computation, communication, and deployment layers. RRAM based in memory computing suffers from scalability limitations due to device non idealities and fixed array sizes. Decentralized AI frameworks struggle with memory efficiency across NAT constrained …
us, cn (code pays fourni par la source)
0 citations
arXiv (Cornell University)
Memory-Guided Unified Hardware Accelerator for Mixed-Precision Scientific Computing
Chuanzhen Wang, Leo Yu Zhang, Eric Liu
Recent hardware acceleration advances have enabled powerful specialized accelerators for finite element computations, spiking neural network inference, and sparse tensor operations. However, existing approaches face fundamental limitations: (1) finite element methods lack comprehensive rounding error analysis for reduced-precision implementations and use fixed …
0 citations
arXiv (Cornell University)
Memory-Guided Unified Hardware Accelerator for Mixed-Precision Scientific Computing
Chuanzhen Wang, Leo Yu Zhang, Eric Liu
Recent hardware acceleration advances have enabled powerful specialized accelerators for finite element computations, spiking neural network inference, and sparse tensor operations. However, existing approaches face fundamental limitations: (1) finite element methods lack comprehensive rounding error analysis for reduced-precision implementations and use fixed …
cn (code pays fourni par la source)
0 citations
arXiv (Cornell University)
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