This was presented by Kate Krontiris (Omidyar
Network, USA) at the Impacts of Civic Technology Conference (TICTeC2016) in Barcelona on 27th April. You can find out more information about the conference here: https://www.mysociety.org/research/tictec-2016/
The digital divide and civic tech (TICTec 2016, Helen Milner)Helen Milner
Civic tech can't make the impact it needs to if those working in the sector don't understand that more than half of the world's population doesn't use the internet. Blending my knowledge of digital exclusion, digital inclusion and the digital divide, and my time on the Speaker's Commission for Digital Democracy, this speech asks some difficult questions about how we can work in partnership to make real impact for the people who need better democracies and better lives.
This was presented by Kate Krontiris (Omidyar
Network, USA) at the Impacts of Civic Technology Conference (TICTeC2016) in Barcelona on 27th April. You can find out more information about the conference here: https://www.mysociety.org/research/tictec-2016/
The digital divide and civic tech (TICTec 2016, Helen Milner)Helen Milner
Civic tech can't make the impact it needs to if those working in the sector don't understand that more than half of the world's population doesn't use the internet. Blending my knowledge of digital exclusion, digital inclusion and the digital divide, and my time on the Speaker's Commission for Digital Democracy, this speech asks some difficult questions about how we can work in partnership to make real impact for the people who need better democracies and better lives.
February 2014 update: Since publishing our original report in December, 2013, we've received dozens of emails from peers in the budding civic tech community proposing additions. On Feb. 26, we released an updated version of the civic tech investment analysis, which includes an additional 34 companies and $265 million of investment. Find out more at http://kng.ht/1cPi3Ar.
Investments by private capital funders and foundations in technology that spurs citizen engagement, improves cities and makes governments more effective is growing significantly, with more than $430 million going to the field between January 2011 and May 2013, according to a major report released today by the John S. and James L. Knight Foundation.
The first report of its kind, “The Emergence of Civic Tech: Investments in a Growing Field,” provides an in-depth analysis of the current state of private capital and foundation investments in civic technology. It aims to help organizations and investors better understand civic tech funding, so that they can strengthen their work and help shape the field. The analysis applies a new approach to research and advances the use of data in the social sector; it showcases an interactive data visualization map that allows users to explore investments across multiple areas of civic tech. Find out more at www.knightfoundation.org/features/civictech
[SEN#7] Le Top 100 des entreprises qui recrutent dans le numériqueFrenchWeb.fr
Au total, les entreprises qui figurent dans le Top 100 des entreprises qui recrutent dans le numérique ont prévu de recruter près de 10 800 profils digitaux d'ici la fin de l'année 2017. 83% de ces recrutements sont prévus en CDI, et 63% correspondent à des créations de postes.
【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。
セル生産方式におけるロボットの活用には様々な問題があるが,その一つとして 3 体以上の物体の組み立てが挙げられる.一般に,複数物体を同時に組み立てる際は,対象の部品をそれぞれロボットアームまたは治具でそれぞれ独立に保持することで組み立てを遂行すると考えられる.ただし,この方法ではロボットアームや治具を部品数と同じ数だけ必要とし,部品数が多いほどコスト面や設置スペースの関係で無駄が多くなる.この課題に対して音𣷓らは組み立て対象物に働く接触力等の解析により,治具等で固定されていない対象物が組み立て作業中に運動しにくい状態となる条件を求めた.すなわち,環境中の非把持対象物のロバスト性を考慮して,組み立て作業条件を検討している.本研究ではこの方策に基づいて,複数物体の組み立て作業を単腕マニピュレータで実行することを目的とする.このとき,対象物のロバスト性を考慮することで,仮組状態の複数物体を同時に扱う手法を提案する.作業対象としてパイプジョイントの組み立てを挙げ,簡易な道具を用いることで単腕マニピュレータで複数物体を同時に把持できることを示す.さらに,作業成功率の向上のために RGB-D カメラを用いた物体の位置検出に基づくロボット制御及び動作計画を実装する.
This paper discusses assembly operations using a single manipulator and a parallel gripper to simultaneously
grasp multiple objects and hold the group of temporarily assembled objects. Multiple robots and jigs generally operate
assembly tasks by constraining the target objects mechanically or geometrically to prevent them from moving. It is
necessary to analyze the physical interaction between the objects for such constraints to achieve the tasks with a single
gripper. In this paper, we focus on assembling pipe joints as an example and discuss constraining the motion of the
objects. Our demonstration shows that a simple tool can facilitate holding multiple objects with a single gripper.