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 88268850 of 10420 papers

TitleStatusHype
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to ATARI gamesCode0
On evaluating CNN representations for low resource medical image classification0
A geometry-inspired decision-based attackCode0
Improving Sample Complexity with Observational Supervision0
Micro-Batch Training with Batch-Channel Normalization and Weight StandardizationCode0
The LogBarrier adversarial attack: making effective use of decision boundary informationCode0
Automated Classification of Histopathology Images Using Transfer LearningCode0
Joint Learning of Discriminative Low-dimensional Image Representations Based on Dictionary Learning and Two-layer Orthogonal Projections0
Efficiently utilizing complex-valued PolSAR image data via a multi-task deep learning framework0
1D-Convolutional Capsule Network for Hyperspectral Image Classification0
sharpDARTS: Faster and More Accurate Differentiable Architecture SearchCode0
Enhancing Generalization of First-Order Meta-Learning0
Evolving Deep Neural Networks by Multi-objective Particle Swarm Optimization for Image ClassificationCode0
Calibrated Top-1 Uncertainty estimates for classification by score based modelsCode0
Learning Disentangled Representations of Satellite Image Time Series0
Convolution with even-sized kernels and symmetric paddingCode0
Deep Octonion Networks0
Class-incremental Learning via Deep Model ConsolidationCode0
Low-Rank Discriminative Least Squares Regression for Image Classification0
Probabilistic End-to-end Noise Correction for Learning with Noisy LabelsCode0
Fisher Discriminative Least Squares Regression for Image ClassificationCode0
An Effective Label Noise Model for DNN Text Classification0
Complex Scene Classification of PolSAR Imagery based on a Self-paced Learning Approach0
Domain Generalization by Solving Jigsaw PuzzlesCode0
Improving Strong-Scaling of CNN Training by Exploiting Finer-Grained Parallelism0
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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
5DaViT-HTop 1 Accuracy90.2Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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