This session, led by James Hamilton, VP and Distinguished Engineer, gives an insider view of some the innovations that help make the AWS cloud unique. He will show examples of AWS networking innovations from the interregional network backbone, through custom routers and networking protocol stack, all the way down to individual servers. He will show examples from AWS server hardware, storage, and power distribution and then, up the stack, in high scale streaming data processing. James will also dive into fundamental database work AWS is delivering to open up scaling and performance limits, reduce costs, and eliminate much of the administrative burden of managing databases. Join this session and walk away with a deeper understanding of the underlying innovations powering the cloud.
AWS Black Belt Online Seminarの最新コンテンツ: https://aws.amazon.com/jp/aws-jp-introduction/#new
過去に開催されたオンラインセミナーのコンテンツ一覧: https://aws.amazon.com/jp/aws-jp-introduction/aws-jp-webinar-service-cut/
This session, led by James Hamilton, VP and Distinguished Engineer, gives an insider view of some the innovations that help make the AWS cloud unique. He will show examples of AWS networking innovations from the interregional network backbone, through custom routers and networking protocol stack, all the way down to individual servers. He will show examples from AWS server hardware, storage, and power distribution and then, up the stack, in high scale streaming data processing. James will also dive into fundamental database work AWS is delivering to open up scaling and performance limits, reduce costs, and eliminate much of the administrative burden of managing databases. Join this session and walk away with a deeper understanding of the underlying innovations powering the cloud.
AWS Black Belt Online Seminarの最新コンテンツ: https://aws.amazon.com/jp/aws-jp-introduction/#new
過去に開催されたオンラインセミナーのコンテンツ一覧: https://aws.amazon.com/jp/aws-jp-introduction/aws-jp-webinar-service-cut/
【DLゼミ】XFeat: Accelerated Features for Lightweight Image Matchingharmonylab
公開URL:https://arxiv.org/pdf/2404.19174
出典:Guilherme Potje, Felipe Cadar, Andre Araujo, Renato Martins, Erickson R. ascimento: XFeat: Accelerated Features for Lightweight Image Matching, Proceedings of the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2023)
概要:リソース効率に優れた特徴点マッチングのための軽量なアーキテクチャ「XFeat(Accelerated Features)」を提案します。手法は、局所的な特徴点の検出、抽出、マッチングのための畳み込みニューラルネットワークの基本的な設計を再検討します。特に、リソースが限られたデバイス向けに迅速かつ堅牢なアルゴリズムが必要とされるため、解像度を可能な限り高く保ちながら、ネットワークのチャネル数を制限します。さらに、スパース下でのマッチングを選択できる設計となっており、ナビゲーションやARなどのアプリケーションに適しています。XFeatは、高速かつ同等以上の精度を実現し、一般的なラップトップのCPU上でリアルタイムで動作します。