Search Results for "java image segmentation"
Sort By:
Showing 4 open source projects for "java image segmentation"
View related business solutions-
Level Up Your Cyber Defense with External Threat ManagementMove beyond alerts. Gain full visibility, context, and control over your external attack surface to stay ahead of every threat.
-
Skillfully - The future of skills based hiringSkillfully transforms hiring through AI-powered skill simulations that show you how candidates actually perform before you hire them. Our platform helps companies cut through AI-generated resumes and rehearsed interviews by validating real capabilities in action. Through dynamic job specific simulations and skill-based assessments, companies like Bloomberg and McKinsey have cut screening time by 50% while dramatically improving hire quality.
-
1
XRichText
An Android rich text class library that supports graphic & text mixing
An Android-rich text class library that supports graphic and text mixing, supports editing and previewing and supports inserting and deleting pictures. Use ScrollView as the outermost layout containing LineaLayout, filled with TextView and ImageView. When deleting, delete the TextView and ImageView according to the position of the cursor, and the text will be automatically merged. The generated data is a list collection, and the data format can be customized. Version V1.4 opens the image... -
2
Content adaptation platform that adapts internet content to any mobile device in real time. Includes features such as device detection, image transcoding, DOM manipulation, XML/RSS feed support and much more.
-
3
JAVA tool for creating html image maps. It's possible to load a picture and create rectangles, circles and polygons. Additionally, content for href, alt and title can be set.
-
4
The Nheengatu Project is a Java library that provides HTML markup abstraction allowing you to reutilize it to generate PDF files, OpenOffice documents, image files, etc. The goal of this project is to maximize the use of HTML markup procedures.
-
Create and run cloud-based virtual machines.Computing infrastructure in predefined or custom machine sizes to accelerate your cloud transformation. General purpose (E2, N1, N2, N2D) machines provide a good balance of price and performance. Compute optimized (C2) machines offer high-end vCPU performance for compute-intensive workloads. Memory optimized (M2) machines offer the highest memory and are great for in-memory databases. Accelerator optimized (A2) machines are based on the A100 GPU, for very demanding applications.
- Previous
- You're on page 1
- Next
