Abstract: A method includes obtaining first data including a first identifier of a first product determine in association with a content item based on first metadata of the content item. The method further includes obtaining a first confidence value associated with the first product and the content item. The method further includes obtaining second data including a second identifier of the first product and a second confidence value. The method further includes providing the first data and the second data to a trained machine learning model. The method further includes obtaining a third confidence value from the trained machine learning model associated with the first product. The method further includes adjusting second metadata of the content item in view of the third confidence value.

Abstract: Methods and systems for time marking of media items at a platform using machine-learning are provided herein. An indication of a identified media item is provided as input to a machine-learning model and one or more outputs of the machine-learning model is obtained. The one or more obtained outputs comprise time marks identifying each of the plurality of content segments of the media item. Each of the plurality of content segments is associated with a segment start indicator for a timeline of the media item. A resulting duration is determined of a combination of the plurality of content segments for which the time marks were obtained from the one or more of outputs of the machine-learning model. Responsive to determining that the resulting duration is less than the duration of the media item, one or more further inputs is provided to the machine learning model.

Abstract: Methods and systems for predicting titles for contents segments of media items at a platform using machine-learning are provided herein. A media item is provided to users of a platform, the media item having a plurality of content segments comprising a first content segment and a second content segment preceding the first content segment in the media item. The first content segment and a title of the second content segment are provided as input to a machine-learning model trained to predict a title for the first content segment that is consistent with the title of the second content segment. One or more outputs of the machine-learning model are obtained which indicate the title for the first content segment. An indication of each content segment and a respective title of each content segment are provided for presentation to at least one user of the one or more users.

Abstract: Methods and systems for time marking of media items at a platform using machine-learning are provided herein. A media item is provided to users of a platform. An indication of the identified media item is provided as input to a machine-learning model that is trained using different feature types of historical media items to predict a plurality of content segments of a given media item each depicting, to the one or more users, a distinct section of the media item. One or more outputs of the machine-learning model are obtained comprising time marks identifying each of the plurality of content segments of the media item. Each of the plurality of content segments are associated with a segment start indicator for a timeline of the media item. The media item and an indication of each segment start indicator is provided for presentation to at least one user.

Abstract: Various embodiments provide methods and systems for providing a recommended volume level in presentation of media content. In some embodiments, volume adjustment events made by a user and/or similar users while watching media content can be detected and automatically recorded. The media content may include a plurality of segments. A normalized volume level for at least one segment of the media content can be determined by aggregating the recorded volume adjustment events corresponding to the at least one segment of the media content. When the media content is played back on a user device, at least some embodiments cause the at least one segment of the media content to be played back at a recommended volume level determined based at least in part upon one of the normalized audio level of the corresponding segment, the audio system of the user device, or historical data and personal profile of the user.

Abstract: Various approaches enable a user to capture image information (e.g., still images or video) about an object of interest such as the sole of a shoe or other piece of footwear (e.g., a sandal) and receive information about items that are determined to match footwear based at least in part on the image information. For example, an image analyze service or other similar service can analyze the images to determine a type of shoe included within the images based at least in part on patterns of other distinguishing features of the sole of the shoe. The image analysis service can aggregate the results and can provide information about the results as a set of matches or results to be displayed to a user in response to a visual search query. The information can include, for example, descriptions, contact information, availability, location data, pricing information, and other such information.

Abstract: Various approaches enable a user to capture image information (e.g., still images or video) about an object of interest such as the sole of a shoe or other piece of footwear (e.g., a sandal) and receive information about items that are determined to match footwear based at least in part on the image information. For example, an image analyze service or other similar service can analyze the images to determine a type of shoe included within the images based at least in part on patterns of other distinguishing features of the sole of the shoe. The image analysis service can aggregate the results and can provide information about the results as a set of matches or results to be displayed to a user in response to a visual search query. The information can include, for example, descriptions, contact information, availability, location data, pricing information, and other such information.

Abstract: A wafer cleaning device comprising a wafer stage for holding a wafer having a surface to be washed, a first nozzle positioned above the wafer, a second nozzle positioned above the wafer. A first height is between the first nozzle and the surface and a second height is between the second nozzle and the surface, wherein the first height is shorter than the second height.

Abstract: A wafer cleaning device comprising a wafer stage for holding a wafer having a surface to be washed, a first nozzle positioned above the wafer, a second nozzle positioned above the wafer. A first height is between the first nozzle and the surface and a second height is between the second nozzle and the surface, wherein the first height is shorter than the second height.

Abstract: A wafer cleaning device comprising a wafer stage for holding a wafer having a surface to be washed, a first nozzle positioned above the wafer, a second nozzle positioned above the wafer. A first height is between the first nozzle and the surface and a second height is between the second nozzle and the surface, wherein the first height is shorter than the second height.

Abstract: An iterative rinse for fabrication of semiconductor devices is described. The iterative rinse includes a plurality of rinse cycles, wherein each of the plurality of rinse cycles has a different resistivity. The plurality of rinse cycles may include a first rinse of a semiconductor substrate with de-ionized (DI) water and carbon dioxide (CO2), followed by a second rinse the semiconductor substrate with DI water and CO2. The first rinse has a first resistivity; the second rinse has a second resistivity lower than the first resistivity.

Abstract: An iterative rinse for fabrication of semiconductor devices is described. The iterative rinse includes a plurality of rinse cycles, wherein each of the plurality of rinse cycles has a different resistivity. The plurality of rinse cycles may include a first rinse of a semiconductor substrate with de-ionized (DI) water and carbon dioxide (CO2), followed by a second rinse the semiconductor substrate with DI water and CO2. The first rinse has a first resistivity; the second rinse has a second resistivity lower than the first resistivity.

Abstract: A wafer cleaning device comprising a wafer stage for holding a wafer having a surface to be washed, a first nozzle positioned above the wafer, a second nozzle positioned above the wafer. A first height is between the first nozzle and the surface and a second height is between the second nozzle and the surface, wherein the first height is shorter than the second height.