Volume 13 Number 1 - International Conference on Computer Science and Machine Learning (CSML 2023)

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Volume 13, Number 1, January 2023

International Conference on Computer Science and Machine Learning (CSML 2023), January 02 ~ 03, 2023, Zurich, Switzerland

Volume Editors : David C. Wyld, Dhinaharan Nagamalai (Eds)
ISBN : 978-1-925953-84-8

Accelerating Experience Replay for Deep Q-Networks with Reduced Target Computation

Bob Zigon¹ and Fengguang Song², ¹Beckman Coulter, USA, ²Indiana University-Purdue University, USA

Machine-Learning Prediction of the Computed Band Gaps of Double Perovskite Materials

Junfei Zhang¹, Yueqi Li² and Xinbo Zhou³, ¹The University of Melbourne, Australia, ²Xiamen University, China, ³Beijing University of Technology, China

Models4Artist: An Intelligent Pose-based Image Search Engine to Assist Artist Creation using Artificial Intelligence and Post Estimate

HuiBing Xie¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA

An Empirical Evaluation of Writing Style Features in Cross-Topic and Cross-Genre Documents in Authorship Identification

Simisani Ndaba, Edwin Thuma and Gontlafetse Mosweunyane, University of Botswana, Botswana

Newly Discovered Route Takeover and DNS Hijacking Attacks in Openshift

Luiza Nacshon¹ and Martin Ukrop², ¹Senior Security Engineer, Red Hat, Israel, ²Senior Technical Program Manager, Red Hat, Czech Republic

Personalized Progressive Federated Learning with Leveraging Client-Specific Vertical Features

Tae Hyun Kim, Won Seok Jang, Sun Cheol Heo, MinDong Sung, and Yu Rang Park, Yonsei University College of Medicine, South Korea

Predicting the Dissolution of Tablets based on Raman Maps using a Linear Regression Model

Gábor Knyihár, Kristóf Csorba and Hassan Charaf, Budapest University of Technology and Economics Budapest, Hungary

A Mobile Application to Mark Attendance using a Combined Backend of the Firestore Database and Amazon AWS Services

Andy Jiang¹ and Yu Sun², ¹USA, ²California State Polytechnic University, USA