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    • 1. 发明专利
    • CMOS IMAGER WITH LIGHT SHIELD BODY
    • JP2001007308A
    • 2001-01-12
    • JP2000134972
    • 2000-05-08
    • ITERIS INC
    • CATHY L BOONE
    • H01L27/14H01L27/146H01L31/10H04N5/335
    • PROBLEM TO BE SOLVED: To obtain a CMOS imager which is improved so as not to be subjected to distortion of an image output in an outdoor illumination environment, by a method wherein a light cutoff layer is formed at least on the light sensing part of a readout circuit without covering a sensing element array. SOLUTION: The light sensing and readout circuit of a sensor 10 is constituted preferably as one integrated circuit or one chip 20. In the image sensing chip 20, an image sensing element center array 22 for an image pixel comprising respectively related row addresses and column addresses is contained, and readout circuits 24, 26 are contained. A layer which is composed of a light cutoff material 32 is constituted of the light sensing circuit 26. i.e., a circuit which is provided with a column amplifier and a column readout circuit. The light cutoff layer 32 is separated by a distance D from the sensing element array 22, and the distance D is set to be smaller than the distance between the array 22 and the light sensing circuit 26. The light cutoff layer 32 may be a thin opaque layer, such as a label available on the market, which is bonded to the upper-part surface of a package by an adhesive or by other methods or may be formed of other proper opaque materials.
    • 10. 发明申请
    • MODELING OF SOIL COMPACTION AND STRUCTURAL CAPACITY FOR FIELD TRAFFICABILITY BY AGRICULTURAL EQUIPMENT FROM DIAGNOSIS AND PREDICTION OF SOIL AND WEATHER CONDITIONS ASSOCIATED WITH USER-PROVIDED FEEDBACK
    • 土壤肥力和结构能力建模农用设备的诊断和预测土壤和天气条件与用户提供的反馈相关的现场交通能力建模
    • WO2016134341A1
    • 2016-08-25
    • PCT/US2016/018821
    • 2016-02-20
    • ITERIS, INC.
    • MEWES, JohnSALENTINY, Dustin
    • A01G7/00G06Q10/06G01N33/00
    • G06N5/04G06N5/048
    • A framework for diagnosing and predicting a suitability of soil conditions to various agricultural operations is performed in a combined, multi-part approach for simulating relationships between predictive data and observable outcomes. The framework includes analyzing one or more factors relevant to field trafficability, workability, and suitability for agricultural operations due to the effects of freezing and thawing cycles, and developing artificial intelligence systems to learn relationships between datasets to produce improved indications of trafficability, workability, and forecasts of suitability windows for a particular user, user community, farm, farm group, field, or equipment. The framework also includes a real-time feedback mechanism by which a user can validate or correct these indications and forecasts. The framework may further be configured to override one or more of the soil state assessments to ensure that indicators and forecasts are consistent with the recently-provided feedback.
    • 用于诊断和预测土壤条件适用于各种农业作业的框架是以组合的多部分方法进行的,用于模拟预测数据与可观察结果之间的关系。 该框架包括分析与现场可交通性,可操作性以及由于冷冻和解冻周期的影响而适用于农业操作的一个或多个因素,以及开发人工智能系统来了解数据集之间的关系,以产生可交通性,可操作性和 对特定用户,用户社区,农场,农场组织,场地或设备的适用性窗口的预测。 该框架还包括一个实时反馈机制,通过该机制用户可以验证或更正这些指示和预测。 该框架可以进一步配置为覆盖一个或多个土壤状态评估,以确保指标和预测与最近提供的反馈一致。