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: An electrical connector includes: an insulating housing having a mating face, a card slot recessed from the mating face with a floor face facing the mating face, and two side walls located at opposite sides of the card slot; and two terminal modules retained in the insulating housing, each terminal module including a row of terminals, a conductive plastic, and an insulating plastic, the row of terminals including plural signal terminals and plural grounding terminals, wherein the grounding terminals are partially retained in the conductive plastic and the insulating plastic surrounds and retains the signal terminals and the conductive plastic, thereby forming the terminal module.

Abstract: An electrical connector includes: an insulating housing defining a mating face, a card slot, and two side walls at opposite sides of the card slot, each of the side walls defining signal passageways and grounding passageways; two rows of terminals located on the side walls and each row of terminal including signal terminals in the signal passageways and grounding terminals in the grounding passageways, the terminals including retaining portions retained in the passageways and elastic arms with contacting portions extending into the card slot; and a one-piece inserting member assembled in the insulating housing, wherein the inserting member defines plural first inserting portions inserted in the signal passageways and plural second inserting portions inserted in the grounding passageways, the second inserting portions contact corresponding grounding terminals, respectively, to establish a grounding path.

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: A method for fabricating a transistor includes providing a substrate, having a gate region and a first trench in the substrate at a first side of the gate region; forming a first gate insulating layer, disposed on a first portion of the gate region, opposite to the first trench; forming a second gate insulating layer, disposed on a second portion of the gate region and a first portion of the first trench abutting to the gate region, wherein the second gate insulating layer is thicker than the first gate insulating layer; forming a gate layer, disposed on the first and second gate insulating layers, having a downward protruding portion corresponding to the first trench; forming a first doped region in the substrate at least under the first trench; and forming a second doped region in the substrate at a second side of the gate region.

Abstract: A method for fabricating a transistor includes providing a substrate, having a gate region and a first trench in the substate at a first side of the gate region; forming a first gate insulating layer, disposed on a first portion of the gate region, opposite to the first trench; forming a second gate insulating layer, disposed on a second portion of the gate region and a first portion of the first trench abutting to the gate region, wherein the second gate insulating layer is thicker than the first gate insulating layer; forming a gate layer, disposed on the first and second gate insulating layers, having a downward protruding portion corresponding to the first trench; forming a first doped region in the substrate at least under the first trench; and forming a second doped region in the substrate at a second side of the gate region.

Abstract: A transistor structure includes a substrate, having a gate region and a first trench in the substate at a first side of the gate region. Further, a first gate insulating layer is disposed on a first portion of the gate region, opposite to the first trench. A second gate insulating layer is disposed on a second portion of the gate region and a first portion of the first trench abutting to the gate region, wherein the second gate insulating layer is thicker than the first gate insulating layer. A gate layer is disposed on the first and second gate insulating layers, having a downward protruding portion corresponding to the first trench. A first doped region is in the substrate at least under the first trench. A second doped region is in the substrate at a second side of the gate region.

Abstract: A transistor structure includes a substrate, having a gate region and a first trench in the substrate at a first side of the gate region. Further, a first gate insulating layer is disposed on a first portion of the gate region, opposite to the first trench. A second gate insulating layer is disposed on a second portion of the gate region and a first portion of the first trench abutting to the gate region, wherein the second gate insulating layer is thicker than the first gate insulating layer. A gate layer is disposed on the first and second gate insulating layers, having a downward protruding portion corresponding to the first trench. A first doped region is in the substrate at least under the first trench. A second doped region is in the substrate at a second side of the gate region.

Abstract: Systems and methods of automatically extracting summaries of video content are described herein. A data processing system can access, from a video database, a first video content element including a first plurality of frame. The data processing system can select an intervallic subset of the first plurality of frames of the first video content element. The data processing system can calculate, for each of a plurality of further subsets comprising a predetermined number of frames from the intervallic subset, a score for the further subset. The data processing system can identify, from the plurality of further subsets, a further subset having a highest score. The data processing system can select a portion of the first video content element comprising the frames of the further subset having the highest score. The data processing system can generate a second video content element comprising the selected portion of the first video content element.

Abstract: Systems and methods of automatically extracting summaries of video content are described herein. A data processing system can access, from a video database, a first video content element including a first plurality of frame. The data processing system can select an intervallic subset of the first plurality of frames of the first video content element. The data processing system can calculate, for each of a plurality of further subsets comprising a predetermined number of frames from the intervallic subset, a score for the further subset. The data processing system can identify, from the plurality of further subsets, a further subset having a highest score. The data processing system can select a portion of the first video content element comprising the frames of the further subset having the highest score. The data processing system can generate a second video content element comprising the selected portion of the first video content element.

Abstract: A computer-implemented method for selecting representative frames for videos is provided. The method includes receiving a video and identifying a set of features for each of the frames of the video. The features including frame-based features and semantic features. The semantic features identifying likelihoods of semantic concepts being present as content in the frames of the video. A set of video segments for the video is subsequently generated. Each video segment includes a chronological subset of frames from the video and each frame is associated with at least one of the semantic features. The method generates a score for each frame of the subset of frames for each video segment based at least on the semantic features, and selecting a representative frame for each video segment based on the scores of the frames in the video segment. The representative frame represents and summarizes the video segment.

Abstract: Systems and methods of automatically extracting summaries of video content are described herein. A data processing system can access, from a video database, a first video content element including a first plurality of frame. The data processing system can select an intervallic subset of the first plurality of frames of the first video content element. The data processing system can calculate, for each of a plurality of further subsets comprising a predetermined number of frames from the intervallic subset, a score for the further subset. The data processing system can identify, from the plurality of further subsets, a further subset having a highest score. The data processing system can select a portion of the first video content element comprising the frames of the further subset having the highest score. The data processing system can generate a second video content element comprising the selected portion of the first video content element.

Abstract: A computer-implemented method for selecting representative frames for videos is provided. The method includes receiving a video and identifying a set of features for each of the frames of the video. The features including frame-based features and semantic features. The semantic features identifying likelihoods of semantic concepts being present as content in the frames of the video. A set of video segments for the video is subsequently generated. Each video segment includes a chronological subset of frames from the video and each frame is associated with at least one of the semantic features. The method generates a score for each frame of the subset of frames for each video segment based at least on the semantic features, and selecting a representative frame for each video segment based on the scores of the frames in the video segment. The representative frame represents and summarizes the video segment.

Abstract: Frame-level quality scores for video frames of a video item is determined. A sliding window is applied to the video frames to identify a plurality of groups of the video frames for scoring on a group-level. A plurality of group-level quality scores for the plurality of groups of video frames of the video item is determined using the frame-level quality scores of the video frames. One of the plurality of groups of video frames of the video item is selected based on the plurality of group-level quality scores. A moving thumbnail is created using the selected group of video frames selected based on the respective group level quality score.

Abstract: Frame-level quality scores for video frames of a video item is determined. A sliding window is applied to the video frames to identify a plurality of groups of the video frames for scoring on a group-level. A plurality of group-level quality scores for the plurality of groups of video frames of the video item is determined using the frame-level quality scores of the video frames. One of the plurality of groups of video frames of the video item is selected based on the plurality of group-level quality scores. A moving thumbnail is created using the selected group of video frames selected based on the respective group level quality score.

Abstract: A transistor structure including a substrate, a transistor device, a split buried layer, and a second buried layer is provided. The substrate has a device region. The transistor device is located in the device region. The split buried layer is located under the transistor device in the substrate and includes first buried layers separated from each other. The second buried layer is located under the split buried layer in the substrate and connects the first buried layers. The second buried layer and the split buried layer have a first conductive type. The transistor structure may have a higher breakdown voltage.

Abstract: A transistor structure including a substrate, a transistor device, a split buried layer, and a second buried layer is provided. The substrate has a device region. The transistor device is located in the device region. The split buried layer is located under the transistor device in the substrate and includes first buried layers separated from each other. The second buried layer is located under the split buried layer in the substrate and connects the first buried layers. The second buried layer and the split buried layer have a first conductive type. The transistor structure may have a higher breakdown voltage.

Abstract: A method of generating a moving thumbnail is disclosed. The method includes sampling video frames of a video item. The method further includes determining frame-level quality scores for the sampled video frames. The method also includes determining multiple group-level quality scores for multiple groups of the sampled video frames using the frame-level quality scores of the sampled video frames. The method further includes selecting one of the groups of the sampled video frames based on the multiple group-level quality scores. The method includes creating a moving thumbnail using a subset of the video frames that have timestamps within a range from the start timestamp to the end timestamp.