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 5751–5800 of 10420 papers

TitleStatusHype
Learning Longer-term Dependencies in RNNs with Auxiliary Losses—0
Learning Long Sequences in Spiking Neural Networks—0
Learning Loss for Test-Time Augmentation—0
Learning Mask Invariant Mutual Information for Masked Image Modeling—0
LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images—0
gSwin: Gated MLP Vision Model with Hierarchical Structure of Shifted Window—0
Growing Efficient Deep Networks by Structured Continuous Sparsification—0
Learning More Discriminative Local Descriptors for Few-shot Learning—0
A Hybrid GA-PSO Method for Evolving Architecture and Short Connections of Deep Convolutional Neural Networks—0
GrowCLIP: Data-aware Automatic Model Growing for Large-scale Contrastive Language-Image Pre-training—0
Learning Multiple Non-linear Sub-spaces Using K-RBMs—0
Learning multiple non-mutually-exclusive tasks for improved classification of inherently ordered labels—0
A Hybrid Fully Convolutional CNN-Transformer Model for Inherently Interpretable Medical Image Classification—0
Learning Muti-expert Distribution Calibration for Long-tailed Video Classification—0
Learning of Time-Frequency Attention Mechanism for Automatic Modulation Recognition—0
AC-VAE: Learning Semantic Representation with VAE for Adaptive Clustering—0
Group Sparse Coding—0
Descriptive analysis of computational methods for automating mammograms with practical applications—0
Designing Adaptive Neural Networks for Energy-Constrained Image Classification—0
CowScape: Quantitative reconstruction of the conformational landscape of biological macromolecules from cryo-EM data—0
Group Invariant Deep Representations for Image Instance Retrieval—0
Grouping-By-ID: Guarding Against Adversarial Domain Shifts—0
Learning Receptive Fields for Pooling from Tensors of Feature Response—0
CovXR: Automated Detection of COVID-19 Pneumonia in Chest X-Rays through Machine Learning—0
Attend Who is Weak: Pruning-assisted Medical Image Localization under Sophisticated and Implicit Imbalances—0
Group Based Deep Shared Feature Learning for Fine-grained Image Classification—0
Learning Representations of Graph Data -- A Survey—0
Learning rich optical embeddings for privacy-preserving lensless image classification—0
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations—0
Learning scale-variant and scale-invariant features for deep image classification—0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network—0
COVIDLite: A depth-wise separable deep neural network with white balance and CLAHE for detection of COVID-19—0
Machine Learning-Based Jamun Leaf Disease Detection: A Comprehensive Review—0
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models—0
Deeply Shared Filter Bases for Parameter-Efficient Convolutional Neural Networks—0
Learning Soft Labels via Meta Learning—0
Design of Supervision-Scalable Learning Systems: Methodology and Performance Benchmarking—0
Beyond Image Classification: A Video Benchmark and Dual-Branch Hybrid Discrimination Framework for Compositional Zero-Shot Learning—0
Markerless retro-identification complements re-identification of individual insect subjects in archived image data of biological experiments—0
Learning Structured Inference Neural Networks with Label Relations—0
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models—0
Learning Structures for Deep Neural Networks—0
Learning Subclass Representations for Visually-varied Image Classification—0
Mixer: DNN Watermarking using Image Mixup—0
Accelerated PDEs for Construction and Theoretical Analysis of an SGD Extension—0
Learning task-agnostic representation via toddler-inspired learning—0
Attending Category Disentangled Global Context for Image Classification—0
Learning Task-Independent Game State Representations from Unlabeled Images—0
Zero-shot and Few-shot Learning with Knowledge Graphs: A Comprehensive Survey—0
GROOD: Gradient-Aware Out-of-Distribution Detection—0
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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