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 3081–3090 of 4891 papers

TitleStatusHype
TransCamP: Graph Transformer for 6-DoF Camera Pose Estimation—0
TransDAE: Dual Attention Mechanism in a Hierarchical Transformer for Efficient Medical Image Segmentation—0
Transfer Function Analysis and Implementation of Active Disturbance Rejection Control—0
Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images—0
Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition—0
Transformer-Empowered Actor-Critic Reinforcement Learning for Sequence-Aware Service Function Chain Partitioning—0
Transformers-based architectures for stroke segmentation: A review—0
Transformers in Single Object Tracking: An Experimental Survey—0
Transformers with Joint Tokens and Local-Global Attention for Efficient Human Pose Estimation—0
Transforming Indoor Localization: Advanced Transformer Architecture for NLOS Dominated Wireless Environments with Distributed Sensors—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified