Latest Articles for Image Recognition

This article explores the impact of attacks on machine learning models and defensive strategies.

Learn how group symmetries can enhance classification models in machine learning.

A new method aims to reduce bias in machine learning models for better fairness.

A new method enhances clarity in dialogue through effective referring expressions.

This research aims to create CAPTCHAs that confuse machines but are clear to humans.

MIP-GAF dataset helps analyze social dynamics in images.

Research presents a method to improve image recognition using fewer examples.

New method improves clustering for large datasets using Stochastic Quantization.

This article evaluates sentiment and meaning in image captions.

Research reveals gaps in image classification models when objects are partially hidden.

LPT++ improves object recognition in classes with few examples through advanced techniques.

JourneyBench tests AI models on unusual and fictional images.

Learn how LTN merges machine learning with logical rules for better predictions.

IRASNet enhances automatic recognition in SAR images through innovative techniques.

A breakdown of training AI models using methods inspired by child learning.

A new strategy combines generative and discriminative training in Vision-Language Models.

A new approach to improve satellite image recognition while managing costs.

New method enhances image matching from various camera spectra.

This article discusses improving computer predictions in videos by straightening image sequences.

SuperClass simplifies image and text recognition for easier research access.

Learn how to improve image-text models and reduce common errors.

New tool H-POPE improves accuracy of vision-language models.

A look into how CNNs interpret images and their features.

An overview of Matrix Factorization and its significance in data analysis.

Research proposes methods to find common elements in unaligned multi-modal data.

Improving vehicle identification through advanced techniques and dynamic models.

A new framework enhances identification by generating varied clothing images.

CP-Mix improves image recognition for rare classes using confusion pairing methods.

A new teaching method improves image recognition for computers.

PG-ECAP creates natural-looking patches to confuse computer recognition systems effectively.

A new tool that ensures safe interactions between humans and AI.

A new method uses shapes to improve how computers recognize images.

Machines learn to locate objects in images using innovative techniques.

A look at detailed image descriptions through compositional image captioning.

A method to safeguard AI models from harmful data.

XTRA improves how computers recognize images using less data and resources.

A method allowing models to learn new concepts using only text descriptions.

Learn how to train computers to recognize images without bias.

Boosting robot accuracy in recognizing new images using clever word techniques.

Exploring new methods for data reconstruction in advanced neural networks.