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 5601–5625 of 10420 papers

TitleStatusHype
Lateralized Learning for Multi-Class Visual Classification Tasks—0
Text Descriptions are Compressive and Invariant Representations for Visual Learning—0
LayerCollapse: Adaptive compression of neural networks—0
Benchmark data to study the influence of pre-training on explanation performance in MR image classification—0
Harnessing Increased Client Participation with Cohort-Parallel Federated Learning—0
Cross-Domain Collaborative Learning via Cluster Canonical Correlation Analysis and Random Walker for Hyperspectral Image Classification—0
Layer-Specific Adaptive Learning Rates for Deep Networks—0
Layer-Wise Adaptive Updating for Few-Shot Image Classification—0
Accelerating CNN inference on FPGAs: A Survey—0
LayoutLLM: Large Language Model Instruction Tuning for Visually Rich Document Understanding—0
Leveraging Perceptual Scores for Dataset Pruning in Computer Vision Tasks—0
DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding—0
Cross-domain CNN for Hyperspectral Image Classification—0
LCDet: Low-Complexity Fully-Convolutional Neural Networks for Object Detection in Embedded Systems—0
AI-Based Copyright Detection Of An Image In a Video Using Degree Of Similarity And Image Hashing—0
Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild—0
LC-TTFS: Towards Lossless Network Conversion for Spiking Neural Networks with TTFS Coding—0
LDCA: Local Descriptors with Contextual Augmentation for Few-Shot Learning—0
Leveraging Semi-Supervised Learning to Enhance Data Mining for Image Classification under Limited Labeled Data—0
Hardware/Software co-design with ADC-Less In-memory Computing Hardware for Spiking Neural Networks—0
L_DMI: A Novel Information-theoretic Loss Function for Training Deep Nets Robust to Label Noise—0
LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation—0
Hardware/Software Co-Design of RISC-V Extensions for Accelerating Sparse DNNs on FPGAs—0
Cross-convolutional-layer Pooling for Image Recognition—0
Hardware Architecture of Embedded Inference Accelerator and Analysis of Algorithms for Depthwise and Large-Kernel Convolutions—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