SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3001–3010 of 4891 papers

TitleStatusHype
Five A^+ Network: You Only Need 9K Parameters for Underwater Image EnhancementCode1
Modelling Quasi-Orthographic Captures for Surface Imaging—0
A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture contentCode1
A Dataset Fusion Algorithm for Generalised Anomaly Detection in Homogeneous Periodic Time Series Datasets—0
On enhancing the robustness of Vision Transformers: Defensive DiffusionCode0
DNN-Compressed Domain Visual Recognition with Feature Adaptation—0
MotionBEV: Attention-Aware Online LiDAR Moving Object Segmentation with Bird's Eye View based Appearance and Motion FeaturesCode1
Hierarchically Coherent Multivariate Mixture NetworksCode4
ParamNet: A Dynamic Parameter Network for Fast Multi-to-One Stain NormalizationCode0
Detection and Classification of Pole-like Landmarks for Domain-invariant 3D Point Cloud Map Matching—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified