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
Temporal Convolutional Neural Network for the Classification of Satellite Image Time SeriesCode0
ExpandNets: Linear Over-parameterization to Train Compact Convolutional Networks0
Cross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data0
Evolutionary-Neural Hybrid Agents for Architecture Search0
A Simple Non-i.i.d. Sampling Approach for Efficient Training and Better Generalization0
A New Cervical Cytology Dataset for Nucleus Detection and Image Classification (Cervix93) and Methods for Cervical Nucleus DetectionCode0
Detecting Adversarial Perturbations Through Spatial Behavior in Activation Spaces0
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial AttackCode0
Structured Binary Neural Networks for Accurate Image Classification and Semantic Segmentation0
Single-Label Multi-Class Image Classification by Deep Logistic Regression0
Weakly Supervised Estimation of Shadow Confidence Maps in Fetal Ultrasound Imaging0
Are pre-trained CNNs good feature extractors for anomaly detection in surveillance videos?0
Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological SlidesCode0
A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural NetworksCode0
Sharpen Focus: Learning with Attention Separability and ConsistencyCode0
DeepConsensus: using the consensus of features from multiple layers to attain robust image classificationCode0
Deep Discriminative Learning for Unsupervised Domain Adaptation0
DSCnet: Replicating Lidar Point Clouds with Deep Sensor Cloning0
Image Classification at Supercomputer Scale0
Composite Binary Decomposition Networks0
DropFilter: A Novel Regularization Method for Learning Convolutional Neural Networks0
Exploring the Deep Feature Space of a Cell Classification Neural Network0
Selective Feature Connection Mechanism: Concatenating Multi-layer CNN Features with a Feature Selector0
Drop-Activation: Implicit Parameter Reduction and Harmonic RegularizationCode0
Distortion Robust Image Classification using Deep Convolutional Neural Network with Discrete Cosine Transform0
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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