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 2351–2400 of 10419 papers

TitleStatusHype
argmax centroid—0
Are Visual Recognition Models Robust to Image Compression?—0
Comparative Investigation of Learning Algorithms for Image Classification with Small Dataset—0
Aerial Image Classification in Scarce and Unconstrained Environments via Conformal Prediction—0
Comparative Evaluation of Recent Universal Adversarial Perturbations in Image Classification—0
Are Vision Transformers Robust to Patch-wise Perturbations?—0
Are Vision Transformers Robust to Patch Perturbations?—0
Comparative Analysis of Multiple Deep CNN Models for Waste Classification—0
Comparative Analysis of Lightweight Deep Learning Models for Memory-Constrained Devices—0
Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia—0
Distortion Robust Image Classification using Deep Convolutional Neural Network with Discrete Cosine Transform—0
Distributed Training of Deep Neural Networks with Theoretical Analysis: Under SSP Setting—0
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions—0
Comparative Analysis of Imbalanced Malware Byteplot Image Classification using Transfer Learning—0
AEON: Adaptive Estimation of Instance-Dependent In-Distribution and Out-of-Distribution Label Noise for Robust Learning—0
Comparative Analysis of Different Methods for Classifying Polychromatic Sketches—0
Compact Representation for Image Classification: To Choose or to Compress?—0
A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges—0
A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge—0
A Review of Transformer-Based Models for Computer Vision Tasks: Capturing Global Context and Spatial Relationships—0
WaveMamba: Spatial-Spectral Wavelet Mamba for Hyperspectral Image Classification—0
Compact Feature Learning for Multi-Domain Image Classification—0
Compact & Capable: Harnessing Graph Neural Networks and Edge Convolution for Medical Image Classification—0
A review of Deep learning Techniques for COVID-19 identification on Chest CT images—0
Distillation from heterogeneous unlabeled collections—0
AdvMask: A Sparse Adversarial Attack Based Data Augmentation Method for Image Classification—0
A review of deep learning-based information fusion techniques for multimodal medical image classification—0
A Control Theoretic Framework for Adaptive Gradient Optimizers in Machine Learning—0
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection—0
Communication Efficient SGD via Gradient Sampling With Bayes Prior—0
A Review of Artificial Intelligence Technologies for Early Prediction of Alzheimer's Disease—0
DistilDoc: Knowledge Distillation for Visually-Rich Document Applications—0
Communication-Efficient Federated Distillation—0
A review: Deep learning for medical image segmentation using multi-modality fusion—0
Communication-Efficient Edge AI: Algorithms and Systems—0
High-performance deep spiking neural networks with 0.3 spikes per neuron—0
AdvJND: Generating Adversarial Examples with Just Noticeable Difference—0
StableMamba: Distillation-free Scaling of Large SSMs for Images and Videos—0
Distilling High Diagnostic Value Patches for Whole Slide Image Classification Using Attention Mechanism—0
Communication-Efficient Adaptive Batch Size Strategies for Distributed Local Gradient Methods—0
Communication-Computation Efficient Device-Edge Co-Inference via AutoML—0
Exploring the Interchangeability of CNN Embedding Spaces—0
Committees of deep feedforward networks trained with few data—0
AdvIT: Adversarial Frames Identifier Based on Temporal Consistency in Videos—0
Distance-based Composable Representations with Neural Networks—0
Comment on "Ensemble Projection for Semi-supervised Image Classification"—0
Combining Stochastic Defenses to Resist Gradient Inversion: An Ablation Study—0
A Contrastive Symmetric Forward-Forward Algorithm (SFFA) for Continual Learning Tasks—0
Combining Two Adversarial Attacks Against Person Re-Identification Systems—0
Combining Supervised Learning and Reinforcement Learning for Multi-Label Classification Tasks with Partial Labels—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
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