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

Showing 90769100 of 10420 papers

TitleStatusHype
Distilled Gradual Pruning with Pruned Fine-tuningCode0
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networksCode0
Distance Matters For Improving Performance Estimation Under Covariate ShiftCode0
Distance Based Image Classification: A solution to generative classification's conundrum?Code0
Robust Sensible Adversarial Learning of Deep Neural Networks for Image ClassificationCode0
GPCA: A Probabilistic Framework for Gaussian Process Embedded Channel AttentionCode0
Chair Segments: A Compact Benchmark for the Study of Object SegmentationCode0
Distance-Aware eXplanation Based LearningCode0
DisplaceNet: Recognising Displaced People from Images by Exploiting Dominance LevelCode0
Disentangling Semantic-to-visual Confusion for Zero-shot LearningCode0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic SystemsCode0
MS-RANAS: Multi-Scale Resource-Aware Neural Architecture SearchCode0
RAIN: A Simple Approach for Robust and Accurate Image Classification NetworksCode0
CGRclust: Chaos Game Representation for Twin Contrastive Clustering of Unlabelled DNA SequencesCode0
Improved Training Speed, Accuracy, and Data Utilization Through Loss Function OptimizationCode0
As large as it gets: Learning infinitely large Filters via Neural Implicit Functions in the Fourier DomainCode0
Disentanglement based Active LearningCode0
Cervical Optical Coherence Tomography Image Classification Based on Contrastive Self-Supervised Texture LearningCode0
RMDL: Random Multimodel Deep Learning for ClassificationCode0
Robust Stable Spiking Neural NetworksCode0
Disentangled representations of microscopy imagesCode0
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of AttentionCode0
ALReLU: A different approach on Leaky ReLU activation function to improve Neural Networks PerformanceCode0
Discriminative Unsupervised Feature Learning with Convolutional Neural NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CoCa (finetuned)Top 1 Accuracy91Unverified
2Model soups (BASIC-L)Top 1 Accuracy90.98Unverified
3Model soups (ViT-G/14)Top 1 Accuracy90.94Unverified
4DaViT-GTop 1 Accuracy90.4Unverified
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2Unverified
6DaViT-HTop 1 Accuracy90.2Unverified
7SwinV2-GTop 1 Accuracy90.17Unverified
8MAWS (ViT-6.5B)Top 1 Accuracy90.1Unverified
9Florence-CoSwin-HTop 1 Accuracy90.05Unverified
10RevCol-HTop 1 Accuracy90Unverified