Image Classification

3718 papers with code • 165 benchmarks • 238 datasets

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

Libraries

Use these libraries to find Image Classification models and implementations

Latest papers with no code

Uncertainty-Aware SAR ATR: Defending Against Adversarial Attacks via Bayesian Neural Networks

no code yet • 27 Mar 2024

Adversarial attacks have demonstrated the vulnerability of Machine Learning (ML) image classifiers in Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) systems.

Multi-scale Unified Network for Image Classification

no code yet • 27 Mar 2024

Convolutional Neural Networks (CNNs) have advanced significantly in visual representation learning and recognition.

Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification

no code yet • 26 Mar 2024

Background and objective: Employing deep learning models in critical domains such as medical imaging poses challenges associated with the limited availability of training data.

Assessing the Performance of Deep Learning for Automated Gleason Grading in Prostate Cancer

no code yet • 25 Mar 2024

Overall, this study lays the groundwork for enhanced Gleason grading systems, potentially improving diagnostic efficiency for prostate cancer.

On machine learning analysis of atomic force microscopy images for image classification, sample surface recognition

no code yet • 24 Mar 2024

While this wealth of information can be challenging to analyze using traditional methods, ML provides a seamless approach to this task.

Multi-Task Learning with Multi-Task Optimization

no code yet • 24 Mar 2024

Multi-task learning solves multiple correlated tasks.

Leveraging Deep Learning and Xception Architecture for High-Accuracy MRI Classification in Alzheimer Diagnosis

no code yet • 24 Mar 2024

Exploring the application of deep learning technologies in the field of medical diagnostics, Magnetic Resonance Imaging (MRI) provides a unique perspective for observing and diagnosing complex neurodegenerative diseases such as Alzheimer Disease (AD).

A Deep Learning Architectures for Kidney Disease Classification

no code yet • 23 Mar 2024

Deep learning has become an extremely powerful tool for complex tasks such as image classification and segmentation.

Image Classification with Rotation-Invariant Variational Quantum Circuits

no code yet • 22 Mar 2024

Variational quantum algorithms are gaining attention as an early application of Noisy Intermediate-Scale Quantum (NISQ) devices.

Your Image is My Video: Reshaping the Receptive Field via Image-To-Video Differentiable AutoAugmentation and Fusion

no code yet • 22 Mar 2024

The landscape of deep learning research is moving towards innovative strategies to harness the true potential of data.