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

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Showing 4101–4150 of 10420 papers

TitleStatusHype
Beyond Batch Learning: Global Awareness Enhanced Domain Adaptation—0
Estimating the Generalization in Deep Neural Networks via Sparsity—0
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework—0
DEPICT: Diffusion-Enabled Permutation Importance for Image Classification Tasks—0
2^B3^C: 2 Box 3 Crop of Facial Image for Gender Classification with Convolutional Networks—0
Dependency Decomposition and a Reject Option for Explainable Models—0
Density estimation in representation space to predict model uncertainty—0
Heterogeneous Visual Features Fusion via Sparse Multimodal Machine—0
HEp-2 Cell Image Classification with Deep Convolutional Neural Networks—0
Hermitry Ratio: Evaluating the validity of perturbation methods for explainable deep learning—0
A Classification Leveraged Object Detector—0
Heterogeneous Federated Learning Using Knowledge Codistillation—0
HD-CNN: Hierarchical Deep Convolutional Neural Networks for Large Scale Visual Recognition—0
Tag-based Semantic Features for Scene Image Classification—0
HDF: Hybrid Deep Features for Scene Image Representation—0
Morphological Network: How Far Can We Go with Morphological Neurons?—0
Analytic Expressions for Probabilistic Moments of PL-DNN With Gaussian Input—0
Have Large Vision-Language Models Mastered Art History?—0
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling—0
Better (pseudo-)labels for semi-supervised instance segmentation—0
Dense Bag-of-Temporal-SIFT-Words for Time Series Classification—0
Analysis of the rate of convergence of an over-parametrized convolutional neural network image classifier learned by gradient descent—0
HASeparator: Hyperplane-Assisted Softmax—0
Denoising Mutual Knowledge Distillation in Bi-Directional Multiple Instance Learning—0
Adaptive Step Sizes for Preconditioned Stochastic Gradient Descent—0
Denoised Labels for Financial Time-Series Data via Self-Supervised Learning—0
A Simple Probabilistic Method for Deep Classification under Input-Dependent Label Noise—0
HASA: Hybrid Architecture Search with Aggregation Strategy for Echinococcosis Classification and Ovary Segmentation in Ultrasound Images—0
Hashing on Nonlinear Manifolds—0
Dendrites endow artificial neural networks with accurate, robust and parameter-efficient learning—0
Best Practices in Pool-based Active Learning for Image Classification—0
Demystifying What Code Summarization Models Learned—0
Demystifying Loss Functions for Classification—0
Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images—0
Analysis of Real-Time Hostile Activitiy Detection from Spatiotemporal Features Using Time Distributed Deep CNNs, RNNs and Attention-Based Mechanisms—0
Demystifying Contrastive Self-Supervised Learning: Invariances, Augmentations and Dataset Biases—0
Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification—0
WheaCha: A Method for Explaining the Predictions of Models of Code—0
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization—0
Best of Both Worlds: AutoML Codesign of a CNN and its Hardware Accelerator—0
Lean classical-quantum hybrid neural network model for image classification—0
HFSP: A Hardware-friendly Soft Pruning Framework for Vision Transformers—0
Bespoke vs. Prêt-à-Porter Lottery Tickets: Exploiting Mask Similarity for Trainable Sub-Network Finding—0
Analysis of Explainable Artificial Intelligence Methods on Medical Image Classification—0
Delving into Deep Image Prior for Adversarial Defense: A Novel Reconstruction-based Defense Framework—0
BenthIQ: a Transformer-Based Benthic Classification Model for Coral Restoration—0
Harnessing Increased Client Participation with Cohort-Parallel Federated Learning—0
Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint—0
Delving Deeper Into Astromorphic Transformers—0
Adaptive Smooth Activation for Improved Disease Diagnosis and Organ Segmentation from Radiology Scans—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