18200338. ESTIMATION APPARATUS, MODEL GENERATION APPARATUS, AND ESTIMATION METHOD simplified abstract (NEC Corporation)
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ESTIMATION APPARATUS, MODEL GENERATION APPARATUS, AND ESTIMATION METHOD
Organization Name
Inventor(s)
ESTIMATION APPARATUS, MODEL GENERATION APPARATUS, AND ESTIMATION METHOD - A simplified explanation of the abstract
This abstract first appeared for US patent application 18200338 titled 'ESTIMATION APPARATUS, MODEL GENERATION APPARATUS, AND ESTIMATION METHOD
Simplified Explanation
The estimation apparatus described in the abstract is a system that can estimate the number of target objects in a given region of an image. Here is a simplified explanation of the abstract:
- Acquisition unit acquires an image.
- Estimation unit estimates the number of target objects in a target region of the acquired image using a learned model.
- Input data for the model is an image.
- Output data of the model include likelihood data and numerical data.
- Likelihood data indicate the likelihood of target objects being in partial regions of the image.
- Numerical data indicate the estimated number of target objects in a partial region.
Potential Applications: This technology could be applied in various fields such as object detection in autonomous vehicles, surveillance systems, and medical imaging for tumor detection.
Problems Solved: This technology helps in accurately estimating the number of target objects in an image, which can be challenging and time-consuming when done manually.
Benefits: The benefits of this technology include improved efficiency, accuracy, and speed in identifying and estimating target objects in images.
Potential Commercial Applications: One potential commercial application of this technology could be in the development of software for automated counting and detection tasks in industries such as agriculture, manufacturing, and security.
Possible Prior Art: One possible prior art for this technology could be existing image processing algorithms used for object detection and counting in images.
Unanswered Questions: 1. How does the accuracy of the estimation compare to manual counting methods? 2. What are the limitations of the model when it comes to estimating the number of target objects in complex or cluttered images?
Original Abstract Submitted
An estimation apparatus includes an acquisition unit and an estimation unit. The acquisition unit acquires an image. The estimation unit estimates the number of target objects included in a target region being at least part of the acquired image by using a learned model. Input data of the model are an image. Output data of the model include likelihood data and numerical data. The likelihood data indicate a likelihood of a one or more target objects being included in each of a plurality of partial regions acquired by dividing the image. The numerical data indicate an estimated number of target objects for a partial region estimated to include one or more target objects out of the plurality of partial regions. The estimation unit estimates the number of target objects included in a target region by using the likelihood data and the numerical data.
