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

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Showing 6326–6350 of 10420 papers

TitleStatusHype
Do Convnets Learn Correspondence?—0
Global-to-Local Support Spectrums for Language Model Explainability—0
Global Meets Local: Effective Multi-Label Image Classification via Category-Aware Weak Supervision—0
Mind the Gap: Removing the Discretization Gap in Differentiable Logic Gate Networks—0
Mind the Modality Gap: Towards a Remote Sensing Vision-Language Model via Cross-modal Alignment—0
Global Interaction Modelling in Vision Transformer via Super Tokens—0
MiNet: A Convolutional Neural Network for Identifying and Categorising Minerals—0
Mini-batch graphs for robust image classification—0
Global Feature Guided Local Pooling—0
Convolution goes higher-order: a biologically inspired mechanism empowers image classification—0
Multi-Domain Few-Shot Learning and Dataset for Agricultural Applications—0
Global Deconvolutional Networks for Semantic Segmentation—0
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients—0
Minimizing the Effect of Noise and Limited Dataset Size in Image Classification Using Depth Estimation as an Auxiliary Task with Deep Multitask Learning—0
Minimum Noticeable Difference based Adversarial Privacy Preserving Image Generation—0
Convolutional XGBoost (C-XGBOOST) Model for Brain Tumor Detection—0
A Graph Neural Network Approach for Product Relationship Prediction—0
MultiCrossViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data—0
Advancing Supervised Local Learning Beyond Classification with Long-term Feature Bank—0
MirBot: A collaborative object recognition system for smartphones using convolutional neural networks—0
MirrorCheck: Efficient Adversarial Defense for Vision-Language Models—0
MIRST-DM: Multi-Instance RST with Drop-Max Layer for Robust Classification of Breast Cancer—0
Misaligned orientations of 4f optical neural network for image classification accuracy on various datasets—0
Does deep learning model calibration improve performance in class-imbalanced medical image classification?—0
Asynchronous Hierarchical Federated Learning—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