• SentiSight.ai 图像识别平台

 

SENTISIGHT.AI IMAGE RECOGNITION PLATFORM
INTERACTIVE WEB PLATFORM FOR DEVELOPING AI-BASED APPLICATIONS
A place to build task-specific AI models for image recognition using modern deep-learning techniques. The platform provides capabilities for object detection and image classification.
It is easy to use and automatically performs most of the image-processing tasks. No coding is required.
For more information, see the SentiSight.ai website.

SENTISIGHT.AI图像识别平台
交互式WEB平台开发基于人工智能的应用程序
建立特定任务的人工智能模型,利用现代深度学习技术进行图像识别.该平台提供了目标检测和图像分类功能。
它易于使用,并自动执行大多数图像处理任务.不需要编码。
有关更多信息,请参见SentiSight.ai网站.

 

The interactive environment of SentiSight.ai is designed for training deep-learning models and provides these capabilities:

  • Image labeling toolkit – allows attaching labels to images for image classification, object detection and image segmentation models. An intuitive interface makes labeling faster and easier. Output labels are automatically saved in a format suitable for deep-learning algorithms.
  • Training environment – a model can be trained on the prepared images without any coding via the intuitive user interface.
  • Interactive statistics – information about the model's performance is produced after the training process. Prediction accuracy, precision, recall and many other metrics allow users to measure their models' performance. This information can be immediately viewed and filtered to briefly state how efficient the model is as well as give guidance on its improvement.
  • Online model use – all models trained by a user can be employed to make predictions based on new, previously unseen images. The models can be used online inside the SentiSight.ai platform or via a REST API.

custom project can be ordered if a task seems to be "non-standard" or rather complicated. In this case our experts will take care of the model's setup and training. The user just needs to take care of image labeling.
See the SentiSight.ai website for more information.

SentiSight.ai的交互环境旨在培训深度学习模型,并提供以下功能:

  • 图像标记工具包-允许在图像上附加标签,用于图像分类、目标检测和图像分割模型。直观的界面使标签更快更容易。输出标签自动以适合深入学习算法的格式保存.
  • 训练环境-可以通过直观的用户界面对准备好的图像进行培训,而无需任何编码。
  • 交互统计-关于模型性能的信息是在培训过程之后产生的。预测的准确性,精确性,召回和许多其他指标允许用户衡量他们的模型的性能。可以立即查看和过滤这些信息,以简要说明该模型的效率,并为其改进提供指导。
  • 在线模型使用-用户培训的所有模型都可以用于根据以前未见过的新图像进行预测。这些模型可以在SentiSight.ai平台内在线使用,也可以通过RESTAPI使用。

定制项目如果一项任务似乎是“不标准的”或相当复杂时,我们的专家将负责模型的设置和培训,用户只需处理图像标签即可。
SentiSight.ai网站想了解更多信息。