The first step is to generate an image. You can use any tool to generate an image. I have used Meta AI and Google AI Studio. I generated two images using the simple prompts written below: A dog riding ...

The goal of this task is to segment retail store customers based on their purchase history using K-Means clustering. This helps the business understand buying patterns and tailor marketing strategies ...

A new artificial intelligence (AI) tool could make it much easier-and cheaper-for doctors and researchers to train medical imaging software, even when only a small number of patient scans are ...

Abstract: Cervical cancer ranks as a major cause of death among women globally, making essential for effective treatment. The automated examination of Pap smear images through sophisticated machine ...

Background and objective: Accurate diagnosis of brain tumors significantly impacts patient prognosis and treatment planning. Traditional diagnostic methods primarily rely on clinicians’ subjective ...

The segmentation and classification of breast ultrasound (BUS) images are crucial for the early diagnosis of breast cancer and remain a key focus in BUS image processing. Numerous machine learning and ...

This project implements a multi-task nnU-Net v2 pipeline for pancreas and lesion segmentation from 3D CT scans. The model leverages a shared encoder for feature extraction and dual decoders for ...

Abstract: In this paper, we propose a method for combining audio and video for segmentation and classification. The objective of segmentation is to detect category change point such as news followed ...