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 43514375 of 10420 papers

TitleStatusHype
Fixed-Point Convolutional Neural Network for Real-Time Video Processing in FPGACode0
How to Use Dropout Correctly on Residual Networks with Batch NormalizationCode0
How transfer learning is used in generative models for image classification: improved accuracyCode0
Why Random Pruning Is All We Need to Start SparseCode0
How Do Training Methods Influence the Utilization of Vision Models?Code0
How Flawed Is ECE? An Analysis via Logit SmoothingCode0
Fourier Analysis on Robustness of Graph Convolutional Neural Networks for Skeleton-based Action RecognitionCode0
Homogeneous Learning: Self-Attention Decentralized Deep LearningCode0
Foundation Model Makes Clustering A Better Initialization For Cold-Start Active LearningCode0
Fossil Image Identification using Deep Learning Ensembles of Data Augmented MultiviewsCode0
Enhancing Cross-task Transferability of Adversarial Examples with Dispersion ReductionCode0
Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language ModelsCode0
Histopathological Image Classification using Discriminative Feature-oriented Dictionary LearningCode0
Histopathological Image Classification based on Self-Supervised Vision Transformer and Weak LabelsCode0
Gated Convolutional Networks with Hybrid Connectivity for Image ClassificationCode0
Gated Linear NetworksCode0
HOLMES: HOLonym-MEronym based Semantic inspection for Convolutional Image ClassifiersCode0
High Performance Offline Handwritten Chinese Character Recognition Using GoogLeNet and Directional Feature MapsCode0
Constructing Multiple Tasks for Augmentation: Improving Neural Image Classification With K-means FeaturesCode0
ISLE: An Intelligent Streaming Framework for High-Throughput AI Inference in Medical ImagingCode0
Forget Vectors at Play: Universal Input Perturbations Driving Machine Unlearning in Image ClassificationCode0
High-fidelity Pseudo-labels for Boosting Weakly-Supervised SegmentationCode0
Hierarchical Representations for Efficient Architecture SearchCode0
Improving Ensemble Distillation With Weight Averaging and Diversifying PerturbationCode0
Hierarchical Mask-Enhanced Dual Reconstruction Network for Few-Shot Fine-Grained Image ClassificationCode0
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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