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 5251–5300 of 10420 papers

TitleStatusHype
AiRound and CV-BrCT: Novel Multi-View Datasets for Scene Classification—0
Inference Time Evidences of Adversarial Attacks for Forensic on Transformers—0
Inference with Hybrid Bio-hardware Neural Networks—0
Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention—0
Learnable Pooling Regions for Image Classification—0
InfoDisent: Explainability of Image Classification Models by Information Disentanglement—0
Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A survey—0
Cross-Modal Retrieval Meets Inference:Improving Zero-Shot Classification with Cross-Modal Retrieval—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
Information contraction in noisy binary neural networks and its implications—0
Information Gain Sampling for Active Learning in Medical Image Classification—0
Attentive Feature Reuse for Multi Task Meta learning—0
Exploring Optimal Deep Learning Models for Image-based Malware Variant Classification—0
Informative Class Activation Maps—0
Informative Robust Causal Representation for Generalizable Deep Learning—0
Cross-Modal Mapping: Mitigating the Modality Gap for Few-Shot Image Classification—0
In-Hindsight Quantization Range Estimation for Quantized Training—0
Deep Learning Algorithms with Applications to Video Analytics for A Smart City: A Survey—0
Initialization Noise in Image Gradients and Saliency Maps—0
Accelerating Deep Neural Networks via Semi-Structured Activation Sparsity—0
Initializing Perturbations in Multiple Directions for Fast Adversarial Training—0
In-Memory Nearest Neighbor Search with FeFET Multi-Bit Content-Addressable Memories—0
InPK: Infusing Prior Knowledge into Prompt for Vision-Language Models—0
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Models—0
Inplace knowledge distillation with teacher assistant for improved training of flexible deep neural networks—0
Deep Learning and Medical Imaging for COVID-19 Diagnosis: A Comprehensive Survey—0
Accurate and Resource-Efficient Lipreading with Efficientnetv2 and Transformers—0
InsCon:Instance Consistency Feature Representation via Self-Supervised Learning—0
INsight: A Neuromorphic Computing System for Evaluation of Large Neural Networks—0
Inspector Gadget: A Data Programming-based Labeling System for Industrial Images—0
Inspect Transfer Learning Architecture with Dilated Convolution—0
Hierarchical Vision Transformer with Prototypes for Interpretable Medical Image Classification—0
Hierarchical Transfer Convolutional Neural Networks for Image Classification—0
Instance-based Deep Transfer Learning—0
Deep Learning Approaches for Medical Imaging Under Varying Degrees of Label Availability: A Comprehensive Survey—0
Crossmodal Knowledge Distillation with WordNet-Relaxed Text Embeddings for Robust Image Classification—0
Hierarchical Sparse Attention Framework for Computationally Efficient Classification of Biological Cells—0
Hierarchical Side-Tuning for Vision Transformers—0
Attentive CutMix: An Enhanced Data Augmentation Approach for Deep Learning Based Image Classification—0
AIQViT: Architecture-Informed Post-Training Quantization for Vision Transformers—0
Deep Learning-based automated classification of Chinese Speech Sound Disorders—0
Backdoor Embedding in Convolutional Neural Network Models via Invisible Perturbation—0
Instant Adversarial Purification with Adversarial Consistency Distillation—0
Learned Gradient Compression for Distributed Deep Learning—0
Institutionally Distributed Deep Learning Networks—0
Instruction-ViT: Multi-Modal Prompts for Instruction Learning in ViT—0
Learning Augmentation Network via Influence Functions—0
Integrated perception with recurrent multi-task neural networks—0
Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification—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