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 8501–8550 of 10420 papers

TitleStatusHype
Delving Deeper Into Astromorphic Transformers—0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework—0
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Demystifying Loss Functions for Classification—0
Demystifying What Code Summarization Models Learned—0
Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning—0
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning—0
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification—0
Morphological Network: How Far Can We Go with Morphological Neurons?—0
Density estimation in representation space to predict model uncertainty—0
Dependency Decomposition and a Reject Option for Explainable Models—0
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks—0
Depth Estimation with Simplified Transformer—0
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread—0
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization—0
Depthwise-STFT based separable Convolutional Neural Networks—0
Dermoscopic Image Classification with Neural Style Transfer—0
Descriptive analysis of computational methods for automating mammograms with practical applications—0
Designing Adaptive Neural Networks for Energy-Constrained Image Classification—0
Designing Extremely Memory-Efficient CNNs for On-device Vision Tasks—0
Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network—0
Design of Real-time Semantic Segmentation Decoder for Automated Driving—0
Design of Supervision-Scalable Learning Systems: Methodology and Performance Benchmarking—0
Design Space Exploration of Hardware Spiking Neurons for Embedded Artificial Intelligence—0
Design-time Fashion Popularity Forecasting in VR Environments—0
Detecção da Psoríase Utilizando Visão Computacional: Uma Abordagem Comparativa Entre CNNs e Vision Transformers—0
Detecting Adversarial Attacks in Semantic Segmentation via Uncertainty Estimation: A Deep Analysis—0
Detecting Adversarial Examples in Convolutional Neural Networks—0
Detecting Adversarial Perturbations Through Spatial Behavior in Activation Spaces—0
Detecting Adversarial Perturbations with Saliency—0
Detecting Adversaries, yet Faltering to Noise? Leveraging Conditional Variational AutoEncoders for Adversary Detection in the Presence of Noisy Images—0
Detecting Hypo-plastic Left Heart Syndrome in Fetal Ultrasound via Disease-specific Atlas Maps—0
Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis—0
Detecting Novelties with Empty Classes—0
Detecting Overfitting via Adversarial Examples—0
Detecting Spurious Correlations via Robust Visual Concepts in Real and AI-Generated Image Classification—0
Detecting Visually Relevant Sentences for Fine-Grained Classification—0
Detection and Segmentation of Manufacturing Defects with Convolutional Neural Networks and Transfer Learning—0
Detection Booster Training: A detection booster training method for improving the accuracy of classifiers.—0
Detection of Children Abuse by Voice and Audio Classification by Short-Time Fourier Transform Machine Learning implemented on Nvidia Edge GPU device—0
Detection of concealed cars in complex cargo X-ray imagery using Deep Learning—0
Detection of Degraded Acacia tree species using deep neural networks on uav drone imagery—0
Detection of Non-uniformity in Parameters for Magnetic Domain Pattern Generation by Machine Learning—0
Detection of Plant Leaf Disease Directly in the JPEG Compressed Domain using Transfer Learning Technique—0
DetNet: Design Backbone for Object Detection—0
Developing a Recommendation Benchmark for MLPerf Training and Inference—0
Developing Convolutional Neural Networks using a Novel Lamarckian Co-Evolutionary Algorithm—0
Show:102550
← PrevPage 171 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