February 13, 2026. This webinar describes how Deep Learning methods can be used for object detection and segmentation in high resolution drone imagery using ArcGIS Pro.
A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric ...
Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...
First 4D Radar Automatic Labelling tools using Segment Anything (SA) drivable area segmentation on camera using Deep Learning for Autonomous Vehicle. KAIST-Radar (K-Radar) (provided by 'AVELab') is a ...
Abstract: Medical image segmentation (MIS) plays a vital role in different medical applications like analysis, treatment planning, and diagnosis. However, the segmentation accuracy was lower due to ...
Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Abstract: Deep learning models for medical image segmentation often struggle with task-specific characteristics, limiting their generalization to unseen tasks with new anatomies, labels, or modalities ...
ABSTRACT: In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy ...
1 School of Biomedical Engineering, Sichuan University, Chengdu, China 2 National Clinical Research Center for Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, China ...
Objective: Our research aims to develop an automated method for segmenting brain CT images in healthy 2-year-old children using the ResU-Net deep learning model. Building on this model, we aim to ...