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 57765800 of 10420 papers

TitleStatusHype
Group Based Deep Shared Feature Learning for Fine-grained Image Classification0
Learning Representations of Graph Data -- A Survey0
Learning rich optical embeddings for privacy-preserving lensless image classification0
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations0
Learning scale-variant and scale-invariant features for deep image classification0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network0
COVIDLite: A depth-wise separable deep neural network with white balance and CLAHE for detection of COVID-190
Machine Learning-Based Jamun Leaf Disease Detection: A Comprehensive Review0
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models0
Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks0
Learning Soft Labels via Meta Learning0
Design of Supervision-Scalable Learning Systems: Methodology and Performance Benchmarking0
Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning0
Markerless retro-identification complements re-identification of individual insect subjects in archived image data of biological experiments0
Learning Structured Inference Neural Networks with Label Relations0
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models0
Learning Structures for Deep Neural Networks0
Learning Subclass Representations for Visually-varied Image Classification0
Mixer: DNN Watermarking using Image Mixup0
Accelerated PDEs for Construction and Theoretical Analysis of an SGD Extension0
Learning task-agnostic representation via toddler-inspired learning0
Attending Category Disentangled Global Context for Image Classification0
Learning Task-Independent Game State Representations from Unlabeled Images0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey0
GROOD: Gradient-Aware Out-of-Distribution Detection0
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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