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 6451–6500 of 10420 papers

TitleStatusHype
Learning From Less Data: Diversified Subset Selection and Active Learning in Image Classification Tasks—0
ModelLock: Locking Your Model With a Spell—0
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning—0
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise—0
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent—0
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification—0
Learning from Few Samples: A Survey—0
ModelVerification.jl: a Comprehensive Toolbox for Formally Verifying Deep Neural Networks—0
Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning—0
Learning from Exemplary Explanations—0
Learning from Crowds with Sparse and Imbalanced Annotations—0
Best Practices in Pool-based Active Learning for Image Classification—0
Demystifying What Code Summarization Models Learned—0
Demystifying Loss Functions for Classification—0
Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images—0
Learning from Attacks: Attacking Variational Autoencoder for Improving Image Classification—0
Learning Fine-grained Features via a CNN Tree for Large-scale Classification—0
Learning Filter Pruning Criteria for Deep Convolutional Neural Networks Acceleration—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification—0
Learning Expressive Prompting With Residuals for Vision Transformers—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Learning Embeddings for Image Clustering: An Empirical Study of Triplet Loss Approaches—0
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization—0
Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator—0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms—0
Lean classical-quantum hybrid neural network model for image classification—0
2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks—0
Learning efficient structured dictionary for image classification—0
Diverse Knowledge Distillation (DKD): A Solution for Improving The Robustness of Ensemble Models Against Adversarial Attacks—0
Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding—0
Monotonicity as a requirement and as a regularizer: efficient methods and applications—0
Learning Disentangled Representations of Satellite Image Time Series—0
Monotonic Neural Network: combining Deep Learning with Domain Knowledge for Chiller Plants Energy Optimization—0
Monte Carlo Deep Neural Network Arithmetic—0
Monte-Carlo Sampling applied to Multiple Instance Learning for Histological Image Classification—0
Learning Discriminative Representation via Metric Learning for Imbalanced Medical Image Classification—0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework—0
BenthIQ: a Transformer-Based Benthic Classification Model for Coral Restoration—0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification—0
Learning Discriminative Multilevel Structured Dictionaries for Supervised Image Classification—0
Learning Discriminative Features Via Weights-biased Softmax Loss—0
Rectifying Open-set Object Detection: A Taxonomy, Practical Applications, and Proper Evaluation—0
More Side Information, Better Pruning: Shared-Label Classification as a Case Study—0
Learning Dependency Structures for Weak Supervision Models—0
Learning degraded image classification with restoration data fidelity—0
Delving Deeper Into Astromorphic Transformers—0
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint—0
Learning Deep Optimal Embeddings with Sinkhorn Divergences—0
Learning Deep NBNN Representations for Robust Place Categorization—0
Show:102550
← PrevPage 130 of 209Next →
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