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 7576–7600 of 10420 papers

TitleStatusHype
PROFIT: A Specialized Optimizer for Deep Fine Tuning—0
Initialization Using Perlin Noise for Training Networks with a Limited Amount of Data—0
Deep learning and face recognition: the state of the art—0
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks—0
Initialization Noise in Image Gradients and Saliency Maps—0
Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey—0
In-Hindsight Quantization Range Estimation for Quantized Training—0
Informed Non-convex Robust Principal Component Analysis with Features—0
Deep Learning Algorithms for Early Diagnosis of Acute Lymphoblastic Leukemia—0
Informative Robust Causal Representation for Generalizable Deep Learning—0
Informative Class Activation Maps—0
Information-theoretical label embeddings for large-scale image classification—0
ProjectionNet: Learning Efficient On-Device Deep Networks Using Neural Projections—0
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT—0
Deep Kernel Learning via Random Fourier Features—0
BA^2M: A Batch Aware Attention Module for Image Classification—0
A Method for Restoring the Training Set Distribution in an Image Classifier—0
Information Gain Sampling for Active Learning in Medical Image Classification—0
Information contraction in noisy binary neural networks and its implications—0
Joint Device-Edge Inference over Wireless Links with Pruning—0
Prompt-Guided Adaptive Model Transformation for Whole Slide Image Classification—0
Information Bottleneck-Based Hebbian Learning Rule Naturally Ties Working Memory and Synaptic Updates—0
A Zero-shot Learning Method Based on Large Language Models for Multi-modal Knowledge Graph Embedding—0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Deep Integrated Pipeline of Segmentation Guided Classification of Breast Cancer from Ultrasound Images—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
5DaViT-HTop 1 Accuracy90.2—Unverified
6Meta Pseudo Labels (EfficientNet-L2)Top 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