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 64766500 of 10420 papers

TitleStatusHype
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms0
Lean classical-quantum hybrid neural network model for image classification0
2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks0
Learning efficient structured dictionary for image classification0
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks0
Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding0
Monotonicity as a requirement and as a regularizer: efficient methods and applications0
Learning Disentangled Representations of Satellite Image Time Series0
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization0
Monte Carlo Deep Neural Network Arithmetic0
Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework0
BenthIQ: a Transformer-Based Benthic Classification Model for Coral Restoration0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification0
Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification0
Learning Discriminative Features Via Weights-biased Softmax Loss0
Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation0
More Side Information, Better Pruning: Shared-Label Classification as a Case Study0
Learning Dependency Structures for Weak Supervision Models0
Learning degraded image classification with restoration data fidelity0
Delving Deeper Into Astromorphic Transformers0
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint0
Learning Deep Optimal Embeddings with Sinkhorn Divergences0
Learning Deep NBNN Representations for Robust Place Categorization0
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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
10Meta Pseudo Labels (EfficientNet-B6-Wide)Top 1 Accuracy90Unverified