Abstract: A processor selects a target sheet from a plurality of predetermined sheet candidates in accordance with selection information that is input via an input device. Furthermore, the processor derives feature information regarding a noise point from a target image that is obtained through an image reading process performed on an output sheet output from an image forming device, the noise point being a dot-like noise image included in the target image. Furthermore, the processor determines whether or not the noise point is a dot-like sheet noise by applying the feature information to a determination algorithm that corresponds to the target sheet, the sheet noise being included in a sheet of the output sheet itself, the determination algorithm being one of a plurality of determination algorithms that respectively correspond to the plurality of sheet candidates.

Abstract: An image forming portion applies a bias voltage in which an AC component is superimposed on a DC component between a first carrying member and a second carrying member, and transfers toner from the first carrying member to the second carrying member to form an image on the second carrying member. An AC setting processing portion performs AC calibration to set a magnitude of the AC component of the bias voltage. A potential measurement processing portion measures a surface potential of the first carrying member or the second carrying member based on a target current flowing between the first carrying member and the second carrying member. A drive processing portion executes the AC calibration before measurement of the surface potential in a case where, when measuring the surface potential, an activation condition is satisfied.

Abstract: An image forming apparatus includes a developing device that forms a toner image, by developing an electrostatic latent image formed on a photoconductor drum, a charging device that electrically charges the photoconductor drum, a developing power source that applies a predetermined developing bias voltage to the developing device, and a calculation device that calculates a surface potential of the photoconductor drum, on a basis of the developing current flowing in the developing device. The developing power source applies the developing bias voltage in a plurality of levels, to the developing device. A current measurement device measures a developing current, with respect to the developing bias voltage of each level. The calculation device calculates the surface potential, on the basis of each developing current.

Abstract: An image forming apparatus includes an image carrier, a charging device, a developing device, a transfer device, a development power supply, a current measurement device, and a processor. The development power supply applies a predetermined bias voltage to the developing device. The processor functions as a calculator and a controller. The calculator calculates a surface potential of the image carrier based on the development current measured by the current measurement device. The controller controls the charging device, the developing device, the transfer device, and the development power supply. The controller sets a tentative transfer current to be flowed through the transfer device while the calculator calculates the surface potential.

Abstract: A vector generation unit derives a feature vector of a reference document and a feature vector of a population document. A feature quantity extraction unit performs a dimensionality reduction process to reduce dimensionality of the above feature vectors and sets a dimensional value obtained by the dimensionality reduction process as a first feature quantity, and derives a cosine similarity between the feature vector of the reference document and the feature vector of the population document as a second feature quantity. A retrieval range control unit extracts a specific number of population documents, starting from the population document with the shortest distance to the reference document in a feature quantity space of the first feature quantity, so as to limit a retrieval range. A training data extraction unit extracts, as training data, a specific number of documents from the extracted documents, starting from the document with the lowest cosine similarity.

Abstract: A vector generation unit derives a reference feature vector and a document feature vector. A feature quantity extraction unit performs a dimensionality reduction process on the reference feature vector and the document feature vector so as to set a dimensional value as a first feature quantity and derives a cosine similarity between the reference feature vector and the document feature vector as a second feature quantity. A grid division unit classifies documents into first partial regions obtained by dividing a feature quantity space of the first feature quantity, and classifies the documents into second partial regions obtained by dividing a range of the second feature quantity. A training data extraction unit selects, for each combination of a first partial region and a second partial region, a document classified in both the partial regions and sets documents selected with respect to all combinations as training data.

Abstract: A display control device includes a hardware processor. The hardware processor implements functions of a first operating system, a second operating system, and a hypervisor. The first operating system controls execution of at least one of a first application and a second application. The first application serves to generate a first content image to be displayed on a first display device mounted on a vehicle. The second application serves to generate a second content image to be displayed on a second display device mounted on the vehicle. The second operating system is different from the first operating system. The hypervisor controls execution of the first operating system and the second operating system.

Abstract: An image forming apparatus includes an amorphous silicon photosensitive member, a developing device including a developer carrying member that carries a two-component developer, and a control portion. When a potential difference V0?Vdc between the photosensitive member and the developer carrying member has a first potential difference at which the toner is moved from the developer carrying member to the photosensitive member and a second potential difference at which the toner is moved from the photosensitive member to the developer carrying member, the control portion adjusts V0 or Vdc so that the first potential difference and the second potential difference are equal in value and opposite in polarity, and a first development current |Ia| that flows at the first potential difference and a second development current |Ib| that flows at the second potential difference satisfy 1.9×10?2?|Ib|/N?5.7×103 [?A/mm].

Abstract: An image forming apparatus includes image forming units. A controller includes an execution section, a measurement section, and a prediction section. The execution section controls execution of a developer refresh operation in which toner is ejected from a developer bearing member to an image bearing member so that a specific image forming unit replenishes a development device with the toner from the developer bearing member. The measurement section measures respective surface potentials of the image bearing members included in other image forming units while the specific image forming unit is executing the developer refresh operation. The prediction section uses measurement results of the respective surface potentials of the image bearing members included in the other image forming units for a prediction on the surface potential of the image bearing member included in the specific image forming unit.

Abstract: An image forming apparatus includes: a development device which develops an electrostatic latent image formed on a photosensitive drum into a toner image; a charger which charges the photosensitive drum; a development power supply which applies a prescribed bias voltage to the development device; and a calculating section which calculates a surface potential of the photosensitive drum based on a development current flowing in the development device. The calculating section calculates, as the surface potential, a bias voltage at which a non-charging development current that flows in the development device in an uncharged state in which the charger has not charged the photosensitive drum is equal to a charging development current that flows in the development device in a charged state in which the charger has charged the photosensitive drum.

Abstract: A processor generates an extraction image by extracting, from a test image, a target specific part that is a horizontal stripe extending in a horizontal direction or a noise point. The processor derives a vertical data sequence from a target area in the extraction image and converts the vertical data sequence to primary conversion data of a frequency domain. The processor converts, to secondary conversion data of a space domain, correction data that is obtained by removing, from the primary conversion data, data of frequency bands other than a particular frequency band corresponding to a target specific part that was determined as having periodicities. The processor classifies the target specific parts into periodic specific part and non-periodic specific part by comparing positions of the target specific parts with a peak position in a waveform represented by the secondary conversion data.

Abstract: The image processing apparatus includes: an abnormality detection unit configured to detect one or more abnormalities included in a target image and an abnormality exclusion processing unit configured to exclude a specific abnormality from the detected one or more abnormalities. In a case in which a detection area of a certain abnormality among the detected one or more abnormalities and a detection area of another abnormality overlap with each other and a type of the certain abnormality and a type of the another abnormality are different from each other, when brightness information of one of the certain abnormality and the another abnormality satisfies a specific condition, the abnormality exclusion processing unit excludes the one of the certain abnormality and the another abnormality from the detected one or more abnormalities.

Abstract: An image forming apparatus includes an image carrier, a charging device, a developing device, a developing power source, a current measuring device, and a processor. On a surface of the image carrier, an electrostatic latent image is formed. The charging device electrically charges the image carrier. The developing device forms a toner image, by supplying toner to the image carrier and developing the electrostatic latent image formed on the image carrier. The developing power source applies a predetermined bias voltage to the developing device. The current measuring device measures a developing current flowing in the developing device. The processor acts, by executing a control program, as a calculator that calculates a surface potential of the image carrier, on a basis of the developing current measured by the measuring device.

Abstract: A processor identifies a specific part composed of a plurality of significant pixels in a mixed-color test image. Furthermore, the processor identifies a color vector. The color vector represents a vector in a color space from one of a color of the specific part in the mixed-color test image and a color of a reference area including a periphery of the specific part to the other. Furthermore, the processor determines which of a plurality of image creating portions of an image forming device corresponding to a plurality of developing colors, is a cause of an image defect, based on the color vector identified from the mixed-color test image.

Abstract: An image processing apparatus includes an anomaly detecting unit configured to detect anomalies included in a target image; and an anomaly exclusion processing unit configured to exclude a specific anomaly among the detected anomalies. Further, the anomaly exclusion processing unit excludes one of an anomaly and another anomaly among the detected anomalies, if (a) a detection area of the anomaly, a detection area of the other anomaly, and an overlapping area of the detection areas of the anomaly and the other anomaly satisfy a predetermined condition and (b) a type of the anomaly and a type of the other anomaly are different from each other.

Abstract: An image forming apparatus includes: a development device which develops an electrostatic latent image formed on a photosensitive drum into a toner image; a charger which charges the photosensitive drum; a development power supply which applies a bias voltage to the development device; a calculating section which calculates a surface potential of the photosensitive drum based on a development current flowing in the development device; and an estimating section which estimates a fogging toner amount. The fogging toner amount is an amount of toner moved due to fogging. When the fogging toner amount estimated by the estimating section is less than a prescribed threshold, the calculating section calculates a value of the bias voltage at which the development current stops flowing as the surface potential.

Abstract: Storage (24) stores therein a teacher model (54) that is a target image (50) with a teacher annotation (52), which specifies the target image (50), assigned thereto. An inferring section (32) assigns based on the teacher model (54) an inferred annotation (82) to an inspection image (80) belonging to the same category to which the target image (50) belongs. The inferred annotation (82) is a result of inference from the inspection image (80) based on the teacher model (54). An aiding section (34) aids a human to determine whether or not the inferred annotation (82) specifies the inspection image (80). A correcting section (36) generates a corrected model (86) in a manner to add a corrected annotation (84) to the inferred annotation (82) so that the inspection image (80) is specified.

Abstract: An image recognition method includes a feature amount extracting step of generating, from an input image, a base feature map group including a plurality of base feature maps; an inferring step of deriving a plurality of inference results using each of a plurality of machine-learned inference devices for a plurality of inference inputs based on the base feature map group; and an integrating step of integrating the plurality of inference results by a specific manner to derive a final inference result, where each of the plurality of inference inputs has some or all base feature maps of the plurality of base feature maps, and each of the plurality of inference inputs has the some or all base feature maps that are different in part or whole from the some or all base feature maps of another inference input in the plurality of inference inputs.

Abstract: A processor selects a target sheet from a plurality of predetermined sheet candidates in accordance with selection information that is input via an input device. Furthermore, the processor derives feature information regarding a noise point from a target image that is obtained through an image reading process performed on an output sheet output from an image forming device, the noise point being a dot-like noise image included in the target image. Furthermore, the processor determines whether or not the noise point is a dot-like sheet noise by applying the feature information to a determination algorithm that corresponds to the target sheet, the sheet noise being included in a sheet of the output sheet itself, the determination algorithm being one of a plurality of determination algorithms that respectively correspond to the plurality of sheet candidates.

Abstract: An image processing apparatus includes an anomaly detecting unit, and an anomaly unification processing unit. The anomaly detecting unit is configured to detect anomalies included in a target image. The anomaly unification processing unit is configured to unify specific anomalies among the detected anomalies. Further, if a type of an anomaly among the detected anomalies is the same as a type of another anomaly among the detected anomalies, the anomaly unification processing unit (a) determines whether the anomaly and the other anomaly should be unified or not on the basis of a relationship between a position of the anomaly and a position of the other anomaly, and (b) unifies the anomaly and the other anomaly if it is determined that the anomaly and the other anomaly should be unified.