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Found 11 papers, 3 papers with code
Open3DBench: Open-Source Benchmark for 3D-IC Backend Implementation and PPA Evaluation
This work introduces Open3DBench, an open-source 3D-IC backend implementation benchmark built upon the OpenROAD-flow-scripts framework, enabling comprehensive evaluation of power, performance, area, and thermal metrics.
FedPalm: A General Federated Learning Framework for Closed- and Open-Set Palmprint Verification
To further enhance verification performance, we introduce a Textural Expert Interaction Module that dynamically routes textural features among experts to generate refined side textural features.
Pareto Set Learning for Multi-Objective Reinforcement Learning
Multi-objective decision-making problems have emerged in numerous real-world scenarios, such as video games, navigation and robotics.
Deep Learning in Palmprint Recognition-A Comprehensive Survey
Palmprint recognition has emerged as a prominent biometric technology, widely applied in diverse scenarios.
Neural Solver Selection for Combinatorial Optimization
Machine learning has increasingly been employed to solve NP-hard combinatorial optimization problems, resulting in the emergence of neural solvers that demonstrate remarkable performance, even with minimal domain-specific knowledge.
Beyond First-Order: A Multi-Scale Approach to Finger Knuckle Print Biometrics
Recently, finger knuckle prints (FKPs) have gained attention due to their rich textural patterns, positioning them as a promising biometric for identity recognition.
Scale-aware competition network for palmprint recognition
This paper proposes a scale-aware competitive network (SAC-Net), which includes the Inner-Scale Competition Module (ISCM) and the Across-Scale Competition Module (ASCM) to capture texture characteristics related to orientation and scale.
Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy
Machine learning has been adapted to help solve NP-hard combinatorial optimization problems.
SegNetr: Rethinking the local-global interactions and skip connections in U-shaped networks
Recently, U-shaped networks have dominated the field of medical image segmentation due to their simple and easily tuned structure.
PL-Net: Progressive Learning Network for Medical Image Segmentation
In recent years, segmentation methods based on deep convolutional neural networks (CNNs) have made state-of-the-art achievements for many medical analysis tasks.
Deep learning-based person re-identification methods: A survey and outlook of recent works
In recent years, with the increasing demand for public safety and the rapid development of intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot research topics in the computer vision field.
