Volume-2 Issue-6, October 2022 – Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) https://www.ijainn.latticescipub.com Exploring Innovation | ISSN: 2582-7626 (Online) | A Periodical Journal | Reg. No: C/1383209 | Published by Lattice Science Publication (LSP) Fri, 18 Aug 2023 06:49:52 +0000 en-US hourly 1 https://wordpress.org/?v=7.0 https://www.ijainn.latticescipub.com/wp-content/uploads/2021/01/cropped-IJAINN-logo-WF-32x32.png Volume-2 Issue-6, October 2022 – Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) https://www.ijainn.latticescipub.com 32 32 F1060102622 https://www.ijainn.latticescipub.com/portfolio-item/f1060102622/ Sat, 01 Oct 2022 09:21:14 +0000 https://www.ijainn.latticescipub.com/?post_type=portfolio&p=1011 The Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) has ISSN 2582-7626 (online), open-access, peer-reviewed, periodical bi-monthly international journal, which is published by Lattice Science Publication (LSP) in February, April, June, August, October and December.The aim of the journal is to publish high quality peer–reviewed original articles in the area of Artificial Intelligence and Neural Networking that covers Neural Networks, Fuzzy Logic, Simulated Biological Evolution Algorithms (Like Genetic Algorithm), Ant Colony Optimization, Reasoning and Evolution, Intelligence Applications, Computer Vision and Speech Understanding, Multimedia and Cognitive Informatics, Data Mining and Machine Learning Tools, Heuristic and Ai Planning Strategies and Tools, Computational Theories of Learning, Technology and Computing (Like Particle Swarm Optimization), Intelligent System Architectures, Knowledge Representation, Bioinformatics, Natural Language Processing, Multiagent Systems, Supervised Learning, Unsupervised Learning, Deep Learning, Big Data and AI Approaches, Reinforcement Learning, Learning with Generative Adversarial Networks, Regression and Prediction, Problem Solving and Planning, Clustering, Classification, Neural Information Processing, Vision and Speech Perception, Heterogeneous and Streaming Data, Probabilistic Models and Methods, Reasoning and Inference, Marketing and Social Sciences, Knowledge Discovery, Web Mining, Information Retrieval, Design and Diagnosis, Game Playing, Streaming Data, Music Modelling and Analysis, Robotics and Control, Multi-Agent Systems. #Neural Networks #Fuzzy Logic #Simulated Biological Evolution Algorithms (Like Genetic Algorithm) #Ant Colony Optimization #Reasoning and Evolution #Intelligence Applications #Computer Vision and Speech Understanding #Multimedia and Cognitive Informatics #Data Mining and Machine Learning Tools #Heuristic and AI Planning Strategies and Tools #Computational Theories of Learning #Technology and Computing (Like Particle Swarm Optimization) #Intelligent System Architectures #Knowledge Representation #Bioinformatics #Natural Language Processing #Multiagent Systems #Supervised Learning #Unsupervised Learning #Deep Learning #Big Data and AI Approaches #Reinforcement Learning #Learning with Generative Adversarial Networks #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Probabilistic Models and Methods #Reasoning and Inference #Marketing and Social Sciences #Knowledge Discovery #Web Mining, Information Retrieval #Design and Diagnosis #Game Playing #Streaming Data #Music Modelling and Analysis #Robotics and Control #Multi-Agent systems #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

The post F1060102622 appeared first on Indian Journal of Artificial Intelligence and Neural Networking (IJAINN).

]]> The Indian Journal of Artificial Intelligence and Neural Networking (IJAINN) has ISSN 2582-7626 (online), open-access, peer-reviewed, periodical bi-monthly international journal, which is published by Lattice Science Publication (LSP) in February, April, June, August, October and December.The aim of the journal is to publish high quality peer–reviewed original articles in the area of Artificial Intelligence and Neural Networking that covers Neural Networks, Fuzzy Logic, Simulated Biological Evolution Algorithms (Like Genetic Algorithm), Ant Colony Optimization, Reasoning and Evolution, Intelligence Applications, Computer Vision and Speech Understanding, Multimedia and Cognitive Informatics, Data Mining and Machine Learning Tools, Heuristic and Ai Planning Strategies and Tools, Computational Theories of Learning, Technology and Computing (Like Particle Swarm Optimization), Intelligent System Architectures, Knowledge Representation, Bioinformatics, Natural Language Processing, Multiagent Systems, Supervised Learning, Unsupervised Learning, Deep Learning, Big Data and AI Approaches, Reinforcement Learning, Learning with Generative Adversarial Networks, Regression and Prediction, Problem Solving and Planning, Clustering, Classification, Neural Information Processing, Vision and Speech Perception, Heterogeneous and Streaming Data, Probabilistic Models and Methods, Reasoning and Inference, Marketing and Social Sciences, Knowledge Discovery, Web Mining, Information Retrieval, Design and Diagnosis, Game Playing, Streaming Data, Music Modelling and Analysis, Robotics and Control, Multi-Agent Systems. #Neural Networks #Fuzzy Logic #Simulated Biological Evolution Algorithms (Like Genetic Algorithm) #Ant Colony Optimization #Reasoning and Evolution #Intelligence Applications #Computer Vision and Speech Understanding #Multimedia and Cognitive Informatics #Data Mining and Machine Learning Tools #Heuristic and AI Planning Strategies and Tools #Computational Theories of Learning #Technology and Computing (Like Particle Swarm Optimization) #Intelligent System Architectures #Knowledge Representation #Bioinformatics #Natural Language Processing #Multiagent Systems #Supervised Learning #Unsupervised Learning #Deep Learning #Big Data and AI Approaches #Reinforcement Learning #Learning with Generative Adversarial Networks #Regression and Prediction #Problem Solving and Planning #Clustering #Classification #Neural Information Processing #Vision and Speech Perception #Heterogeneous and Streaming Data #Probabilistic Models and Methods #Reasoning and Inference #Marketing and Social Sciences #Knowledge Discovery #Web Mining, Information Retrieval #Design and Diagnosis #Game Playing #Streaming Data #Music Modelling and Analysis #Robotics and Control #Multi-Agent systems #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

GAN-Generated Terrain for Game AssetsCROSSMARK Color horizontal
Yogendra Sisodia
Yogendra Sisodia, Director, Department of Machine Learning, Conga, Thane (Maharashtra), India.

Manuscript received on 25 September 2022 | Revised Manuscript received on 28 September 2022 | Manuscript Accepted on 15 October 2022 | Manuscript published on 30 October 2022 | PP: 1-3 | Volume-2 Issue-6, October 2022 | Retrieval Number: 100.1/ijainn.F1060102622 | DOI: 10.54105/ijainn.F1060.102622

Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Published by Lattice Science Publication (LSP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Multimedia applications, such as virtual reality models and video games, are increasingly interested in the ability to generate and author realistic virtual terrain automatically. In this paper, the author proposes a pipeline for a realistic two-dimensional terrain authoring framework that is powered by several different generative models that are applied one after the other. Two-dimensional role-playing games will benefit from this ability to create multiple high-resolution terrain variants from a single input image and to interpolate between terrains while keeping the terrains that are generated close to how the data is distributed in the real world.

Keywords: Deep Learning, Generative Adversarial Networks, Pix2Pix, Procedural Content Generation, Terrain Generation.
Scope of the Article: Deep Learning

Download PDF

The post F1060102622 appeared first on Indian Journal of Artificial Intelligence and Neural Networking (IJAINN).

]]>