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 2376–2400 of 10420 papers

TitleStatusHype
Extending CAM-based XAI methods for Remote Sensing Imagery SegmentationCode1
Trainable Noise Model as an XAI evaluation method: application on Sobol for remote sensing image segmentationCode1
An evaluation of pre-trained models for feature extraction in image classification—0
CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense PredictionCode2
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network—0
A Framework for Inference Inspired by Human Memory MechanismsCode1
A Comprehensive Review of Generative AI in Healthcare—0
Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial AttacksCode0
Ajwa or Medjool: a binary balanced dataset to teach machine learning عجوة أو مجدول: مجموعة بيانات متوازنة الصنفين لتدريس تعلم الآلة‏Code0
Learnable Extended Activation Function (LEAF) for Deep Neural NetworksCode0
MVC: A Multi-Task Vision Transformer Network for COVID-19 Diagnosis from Chest X-ray Images—0
PRIME: Prioritizing Interpretability in Failure Mode Extraction—0
SCoRe: Submodular Combinatorial Representation Learning—0
Reconstruction of Patient-Specific Confounders in AI-based Radiologic Image Interpretation using Generative PretrainingCode0
ResBit: Residual Bit Vector for Categorical Values—0
Tell Me a Story! Narrative-Driven XAI with Large Language ModelsCode0
Prototype Generation: Robust Feature Visualisation for Data Independent InterpretabilityCode0
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization—0
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering—0
EWasteNet: A Two-Stream Data Efficient Image Transformer Approach for E-Waste Classification—0
Ultra-low-power Image Classification on Neuromorphic HardwareCode0
Two-Step Active Learning for Instance Segmentation with Uncertainty and Diversity Sampling—0
Logarithm-transform aided Gaussian Sampling for Few-Shot LearningCode0
AutoCLIP: Auto-tuning Zero-Shot Classifiers for Vision-Language ModelsCode0
Enhancing Sharpness-Aware Optimization Through Variance SuppressionCode1
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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
5Meta Pseudo Labels (EfficientNet-L2)Top 1 Accuracy90.2—Unverified
6DaViT-HTop 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
10RevCol-HTop 1 Accuracy90—Unverified