Built an AI-Powered Tool with Semantic Image Segmentation Techniques
Segmented a large number of semantic images to help in developing the AI tool.
The firm is a leading environment consultancy based in the United Kingdom associated with field surveys. The company offers its field survey results to various international laboratories. In the digital realm, the client publishes its survey results on their websites in the form of images. From freshwater to the marine environment, the firm covers all organisms found in the UK.
Besides that, the firm wanted to develop an application with the help of a semantic segmentation process. Hence, the firm decided to outsource the semantic image segmentation process from us, AskDataEntry. We delivered a trial project to the firm and converted the firm into our client accordingly. The main aim of the application was to spot existing ecological threats to aquatic ecosystems. To build that application, the client wanted the support of an efficient partner that could provide semantic image segmentation services.
Importance of Semantic Image Segmentation Services for Environment Consultancy Firms
Image segmentation plays a major role in developing autonomous systems, including AI/ML models. At present, developing Artificial Intelligence-based applications is in a trend where images are an integral part. For example, with the application of proper image segmentation, the AI application can detect objects in real-time. The application of semantic image segmentation is wide, especially for the development of computer vision models. This technology helps tag images under different categories at the pixel level for developing computer vision.
The process of segmenting semantic images is quite complex and involves multiple sub-processes. Therefore, application development companies often image segmentation annotation service. It helps not only costs but also ensures the deployment of proper technology in the system. Professional outsourcing companies use cutting-edge technology to segment images at the pixel levels. Also, they accurately label the pixel data to help automation models imprint visual perceptions. Segmenting semantic images has a lot of applications and with the help of outsourcing the developers can get all of them.
Challenges Faced by Client
To develop an application that can detect aquatic animals, the firm wanted a lot of images. For that, it deployed a dedicated team that collected images from various open sources, which are available on the internet. However, all the images were not of good quality and that's why the firm faced difficulties while segmenting those images. On top of that, the team it has hired is not efficient enough to deal with such critical tasks. For that reason, the firm faced a lot more challenges in the entire process of segmenting images. The main challenges it faced are detailed below;
From the beginning, the firm wanted to develop a system that could detect the threat level of the marine ecosystem. Therefore, it has started developing an AI model that can easily detect different marine animals using computer vision technology. However, for that, the firm needed images in bulk quantity but all in premium quality. Due to the unavailability of a large number of quality images, the team has included some low-quality images in the database. Hence, it created a major challenge for the firm to improve the quality of all images before initiating the semantic image segmentation process.
The internal team of the firm consisted of only a few members but they have been assigned huge tasks. Therefore, the pressure on the team members gradually increased and it fell down their optional output level. The entire process of image segmentation was unnecessarily delayed due to the low productivity of the internal team. Hence, the firm decided to delegate the entire process to any professional outsourcing company.
First of all, the internal team collected all marine-life images which were available on the internet. They visited multiple websites to collect those images and they took the help of digital archives also to find appropriate images. However, resources were limited thus the team included some poor-quality images in the database. This caused a major issue in segmenting poor-quality images and it also reduced the efficiency of the system.
The people at the firm involved in this project were not skilled and not aware of the latest technology. Therefore, they only performed up to the image collection part for this project. The firm had to outsource the rest process, which is image segmentation for this special project.
Custom Solution from AskDataEntry
Like all our image segmentation annotation service projects, we followed a structured process in this project. Removing all the challenges faced by the firm with our formulated solutions was our aim here. By deploying our strategic methods, we performed the segmentation process of the images. In this following way, we delivered our robust solutions to the client's project.
We initiated the project with an initial discussion with the client where we shared some samples from our end. After checking the samples, the client agreed to consult with us for the further process. Hence, we deployed a direct link to communicate with the client to get their requirements in detail. It helped us communicate with the client a far better way to address their challenges.
Initially, we faced some issues in receiving the files from the client as the client used a very old file-transferring method. Therefore, we replaced the old method of file transfer with a new and secure method. We set up a secure FTP (File Transfer Protocol) to ensure the smooth transfer of projects. After receiving the files, we immediately started segregating the images under several categories to ease the project.
The client requested us to initiate a trial project with their provided image to check our service quality. For that, they provided us with 200 images that we had to segment properly for the trial process. We involved 2 members of our team and allocated the images equally to complete the project. They efficiently completed the project within 2 days and hence we delivered the trail project immediately.
To check the proper placement of pixel data, we involve a team of quality experts from our end. The quality expert team consisted of our experienced team members who performed the same work many times. Involvement of them ensured the quality enhancement of the project and ensured quality delivery. Once the quality team assured all the tasks we delivered the project to the designated place where the client preferred.
Jin K Firoz
With the help of the expert team at AskDataEntry, we completed our image segmentation work. The team is very efficient in classing images at the pixel level with the help of cutting-edge technology. We give a complete thumbs up to the services of AskDataEntry.
