Innotescusโ collaborative SaaS platform streamlines the Computer Vision development process via smart data handling, labeling, and annotation capabilities. Additionally, its data visualization and cross-functional collaboration features identify data bias early, improve data accuracy, and enable faster, cost-efficient deployment of high performance AI.
Great product with great support behind it. Even with only a small amount of experience with image annotation, I was able to utilize the various options provided. Highly recommend the training session; I was able to get a crash course on the program that was neither overwhelming nor tedious.
This product has embedded the whole gambit of features in such a miniscule pack and gives lot of flexibility and comfort for the annotator to complete their task. The annotators are pleased by using this product in a continuous basis without much of a stress. They also feel less stress product in this annotation segment.
We used the semantic segmentation function to label irregular patches in our images. The tools provided by the platform made it intuitive and convenient to label images quickly and accurately, especially when compared to other labeling platforms. The Innotescus team was very responsive to our questions and receptive to our feedback. Constant software updates also provide improvements and fixes.
The team could run the images and videos easily and annotate accurately. Quality of annotation is much superior by using innotescus tool and the team is quite impressed with the rendering of the job. It is highly pleasurable for the team to use this tool at the work space.
Innotescus is one of the best annotation tools available in the market. No additional efforts needed to learn the software and it's easy to use for both Beginner and advanced level users. Innotescus offers loaded features like flood fill and superpixel. These tools make annotator life easy. In Innotescus, anyone with average computer knowledge can start to work on Segmentation annotation on the other hand additional learning efforts are required for tools available in the market.
From an annotation perspective: the path tool and the assisted annotation tool are most useful for our needs, and earlier bugs related to these tools appear to be fixed now. The zoom feature is also more user-friendly than earlier in beta testing. One concern earlier in annotation experience was being able to return to already annotated images to fix a mistake or to review: the inclusion of the Work history button seems to meet this need to view what images have been annotated and return to previously annotated images in the batch. The addition of an a confirmation pop-up message before submitting an annotated image is also helpful and helps reduce userย error. During this beta phase, bug reporting on the Innotescus website and email communication about updates and fixes were helpful and efficient. Form the customer support perspective: we do appreciate the added feature that allows you to change object class via right clicking. Overall, the tool is working well for our needs. In addition, the customer support process has been smooth and efficient to the point that several of the requests for new features have been dealt with efficiently, which builds trust on the customer side. Nevertheless, we are sure that there is room to improve. The annotation process is often very inconvenient, especially when a coordinated process is required between several individuals on a team. Fortunately, Innotescus has offered us a set of tools that has streamlined our work in an unbeatable way. Before using the Innotescus platform, we had tried to use open source tools that unfortunately hindered the annotation process, thus seriously affecting the team's productivity level. We also tried a couple of commercial tools, however the learning process was torturous. Fortunately for us, the Innotescus platform brought with it several advantages, including an extremely simple and compressed documentation that conveys exactly what end users need to know when using a tool. This has a direct significant impact on the learning curve that is reflected in the level of productivity of the team. In addition, the various modalities for annotation tasks help to simplify and create a pipeline that is then part of a sophisticated machine learning scheme such as multi-modal. This is largely reflected through the annotations export process in both COCO and Pascal VOC formats. Finally, regarding the management process at the admin level, it is extremely simple and requires very little effort to be able to start assigning roles, create projects, tasks and statistically evaluate the different characteristics of the datasets with which you want to work within a team. . This in turn allows to have a deeper and clearer vision of the characteristics of the data to be processed, and thereby choose techniques and algorithms that better fit those conditions.
As a MarTech startup, Market Ready Index needs to get up-to-speed quickly on the things that make us different. The toolset at Innotescus provides the features we need โ data annotation tools that already make sense to our team โย and that help us demonstrate the real benefits of our system to our customers: a better understanding of their marketing communications.
The extremely responsive interface, combined with the readily available pre-processing and assisted annotation tools allow to focus on what really matters: delivering high quality annotations. Annotation project management is by far easier than other similar alternatives, and project summary information allows diagnosing potential issues or bottlenecks.
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