SOTAVerified

Image Classification

Image Classification is a fundamental task in vision recognition that aims to understand and categorize an image as a whole under a specific label. Unlike object detection, which involves classification and location of multiple objects within an image, image classification typically pertains to single-object images. When the classification becomes highly detailed or reaches instance-level, it is often referred to as image retrieval, which also involves finding similar images in a large database.

Source: Metamorphic Testing for Object Detection Systems

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 8051–8075 of 10420 papers

TitleStatusHype
Kernel computations from large-scale random features obtained by Optical Processing UnitsCode0
Improving the Gating Mechanism of Recurrent Neural NetworksCode0
Improving singing voice separation with the Wave-U-Net using Minimum Hyperspherical EnergyCode0
Abnormal Client Behavior Detection in Federated Learning—0
Boosting Mapping Functionality of Neural Networks via Latent Feature Generation based on Reversible Learning—0
Self-supervised classification of dynamic obstacles using the temporal information provided by videos—0
Recovering Localized Adversarial Attacks—0
Hyperspectral Image Classification Based on Adaptive Sparse Deep Network—0
Boosting Network Weight Separability via Feed-Backward Reconstruction—0
Differentiable Deep Clustering with Cluster Size Constraints—0
Image recognition from raw labels collected without annotatorsCode0
NASIB: Neural Architecture Search withIn Budget—0
MixModule: Mixed CNN Kernel Module for Medical Image Segmentation—0
Semi-supervised Learning using Adversarial Training with Good and Bad Samples—0
Toward Metrics for Differentiating Out-of-Distribution SetsCode0
Reflecting After Learning for Understanding—0
Differentiable Combinatorial Losses through Generalized Gradients of Linear Programs—0
Texture Bias Of CNNs Limits Few-Shot Classification Performance—0
KerCNNs: biologically inspired lateral connections for classification of corrupted images—0
Effect of Superpixel Aggregation on Explanations in LIME -- A Case Study with Biological DataCode0
Deep Sub-Ensembles for Fast Uncertainty Estimation in Image ClassificationCode0
Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms—0
Consistency-based Semi-supervised Active Learning: Towards Minimizing Labeling Cost—0
MUTE: Data-Similarity Driven Multi-hot Target Encoding for Neural Network Design—0
Transfer Learning for Algorithm Recommendation—0
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All datasetsImageNetCIFAR-10CIFAR-100STL-10ObjectNetMNISTSVHNiNaturalist 2018ImageNet ReaLFlowers-102Clothing1Mmini WebVision 1.0

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91—Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98—Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94—Unverified
4DaViT-GTop 1 Accuracy90.4—Unverified
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
7SwinV2-GTop 1 Accuracy90.17—Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1—Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05—Unverified
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90—Unverified