![]() ![]() The reader is cautioned that assumptions used in the preparation of any forward-looking information may prove to be incorrect. Such information can generally be identified by the use of forwarding-looking wording such as "may", "expect", "estimate", "anticipate", "intend", "believe" and "continue" or the negative thereof or similar variations. Forward-looking statements consist of statements that are not purely historical, including any statements regarding beliefs, plans, expectations, or intentions regarding the future. Phone: the TSX Venture Exchange nor its Regulation Services Provider (as that term is defined in the policies of the TSX Venture Exchange) accepts responsibility for the adequacy or accuracy of this release.įorward-Looking Information and StatementsĬertain statements in this news release are forward-looking statements or information for the purposes of applicable Canadian and US securities law. With edgeCore, customers improve their margins and agility by rapidly transforming siloed systems and data across continuously evolving situations in business, technology, and cross-domain operations - helping them achieve the impossible. Global enterprises, service providers, and governments are more profitable when insight and action are united to deliver fluid journeys via the platform's low-code development capability and composable operations. subordinate voting shares remain available for reservation under the Plan.ĮdgeTI helps customers sustain situational awareness and accelerate action with its real-time digital operations software, edgeCore™ that unites multiple software applications and data sources into one immersive experience."") and in accordance with the policies of the TSX Venture Exchange. The Options will vest in equal tranches with 1/3 vesting on the date of grant and 1/3 vesting on each of the following two anniversaries, all on the terms of the Company's stock option plan dated February 1, 2019, as amended (the " ") for a period of five years at an exercise price per share of C$1.40. ") exercisable into 100,000 subordinate voting shares of the Company (the " Connor as Chief Financial Officer, the Company has agreed to grant to him 100,000 options (the " In connection with the appointment of Mr. "On behalf of the Board of Directors, I am very pleased that we were able to attract Geremy to our Company and am looking forward to having him join the management team as we look to address the increasing demand for AI solutions,” states Jim Barrett, edgeTI CEO and Chair. in Economics from Princeton University and an M.B.A. ![]() Prior to joining, he held CEO, CFO and Chief Investment Officer roles at investment, real estate, health care and technology companies such as Attalus Capital, the Philadelphia Group and SharpVue Capital which he cofounded. Geremy Connor brings more than 20 years senior leadership experience in finance, accounting, business development and strategic planning to edgeTI. Connor replaces Jason James, who started as an interim contract CFO in January 2021. Geremy Connor as edgeTI’s new Chief Financial Officer. (“edgeTI”, “Company”, “We”, or “Our”) (TSXV: CTRL, OTCQB: UNFYF, FSE: Q5i) is pleased to announce the appointment of Mr. Squared error of 94.25 on the testing data.ARLINGTON, Va., J(GLOBE NEWSWIRE) - Edge Total Intelligence Inc. In addition, the proposed StackNet also achieves a mean Neurocognitive Prediction Challenge 2019 and achieves a mean squared error ofĨ2.42 on the combined training and validation set with 10-foldĬross-validation. StackNet is tested on a public benchmark Adolescent Brain Cognitive Development Predictions from all previous layers including the input layer. StackNet consists of three layers and 11 models. The extracted feature is the distribution ofĭifferent brain tissues in different brain parcellation regions. Normalization, feature denoising, feature selection, training a StackNet, and ![]() Our framework includes feature extraction, feature Download a PDF of the paper titled Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet, by Po-Yu Kao and 4 other authors Download PDF Abstract: In this work, we utilize T1-weighted MR images and StackNet to predict fluid ![]()
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