This project demonstrates an image recognition model trained using Google Teachable Machine. The model is exported in TensorFlow/Keras format and used in a Python script to classify input images.

This study provides fundamental insights into the mechanisms of visual object categorization in primates through a scalable behavioral framework for assessing category learning and generalization in ...

Abhinav pivoted from a career in banking to pursue his first love in writing. Even while working full-time, he continued contributing as an editor-at-large, a role he has held for more than 7 years. A ...

Semi-supervised learning (SSL) has emerged as a promising paradigm for medical image classification, addressing the critical challenge of limited labeled data in healthcare where expert annotation is ...

This relationship is most tested in residential interiors, where boundaries between rooms are intentionally blurred. Kitchens merge into living areas, hallways become extensions of social space, and ...

Abstract: Few-shot weakly-supervised learning (FSWL) is a promising yet challenging paradigm for whole slide image (WSI) classification, in which only slide-level labels and few slides are available.

Contextual Image Attack (CIA) is a novel image-centric jailbreak method designed to exploit vulnerabilities in Multimodal Large Language Models (MLLMs). Unlike traditional attacks that focus on ...

Abstract: Object detection is a fundamental task in many applications of remote sensing image analysis. Problems such as interclass similarity, intraclass variability, and the existence of ...