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 4371–4380 of 4891 papers

TitleStatusHype
Fast Single Image Dehazing via Multilevel Wavelet Transform based OptimizationCode0
Instance Segmentation of Biological Images Using Harmonic EmbeddingsCode0
Deep Cytometry: Deep learning with Real-time Inference in Cell Sorting and Flow Cytometry—0
Gait Recognition via Disentangled Representation Learning—0
Online Convex Matrix Factorization with Representative RegionsCode0
Preference Neural NetworkCode0
Easy Transfer Learning By Exploiting Intra-domain Structures—0
Metric-Learning based Deep Hashing Network for Content Based Retrieval of Remote Sensing ImagesCode1
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action RecognitionCode0
Person Identification with Visual Summary for a Safe Access to a Smart Home—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified