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 34763500 of 10420 papers

TitleStatusHype
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency MapsCode0
S4L: Self-Supervised Semi-Supervised LearningCode0
Deep Hybrid Architecture for Very Low-Resolution Image Classification Using Capsule AttentionCode0
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of AttentionCode0
Improving (α, f)-Byzantine Resilience in Federated Learning via layerwise aggregation and cosine distanceCode0
Improving Generalizability of Kolmogorov-Arnold Networks via Error-Correcting Output CodesCode0
Input Invex Neural NetworkCode0
DeepGraviLens: a Multi-Modal Architecture for Classifying Gravitational Lensing DataCode0
eGAN: Unsupervised approach to class imbalance using transfer learningCode0
EG-Booster: Explanation-Guided Booster of ML Evasion AttacksCode0
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed TrainingCode0
Deep Gradient Compression Reduce the Communication Bandwidth For distributed TraningCode0
Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid RegularizationCode0
Improved Gradient based Adversarial Attacks for Quantized NetworksCode0
Deep Generative Classifiers for Thoracic Disease Diagnosis with Chest X-ray ImagesCode0
Local Relation Networks for Image RecognitionCode0
DeepFool: a simple and accurate method to fool deep neural networksCode0
Improved efficient capsule network for Kuzushiji-MNIST benchmark dataset classificationCode0
Importance of Disjoint Sampling in Conventional and Transformer Models for Hyperspectral Image ClassificationCode0
A Vision-Language Foundation Model for Leaf Disease IdentificationCode0
Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time DetectionCode0
Soft ascent-descent as a stable and flexible alternative to floodingCode0
Elucidating Meta-Structures of Noisy Labels in Semantic Segmentation by Deep Neural NetworksCode0
A Mathematical Framework, a Taxonomy of Modeling Paradigms, and a Suite of Learning Techniques for Neural-Symbolic SystemsCode0
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
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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