Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Gupta, Priyanka; Monga, Suhasini; Logeshwaran, J.; Kaur, Damandeep Title A name given to the resource Converging Deep Learning and Cloud Computing: A Scalable and Efficient Approach for Modern AI Infrastructure Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 2nd International Conference on Advanced Computing and Emerging Technologies, ACET 2025; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/ACET67282.2025.11430377" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/ACET67282.2025.11430377</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105037953850?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105037953850?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Gupta P., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Monga S., Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India; Logeshwaran J., Christ University, Department of Computer Science, Karnataka, Bengaluru, India; Kaur D., Chandigarh University, Department of Computer Science Engineering, Punjab, Mohali, India Description An account of the resource Deep learning has proven to be a powerful approach to solving challenging problems, ranging from natural language processing, speech recognition, to computer vision. The proposed model has capable of matching the expanding amount of facts as well as complexity of the algorithms is demands of deep researching methodologies. These demands cannot be met with traditional computing environments. This is why cloud computing technologies have developed, offering a scalable and affordable alternative for executing deep learning algorithms. Cloud computing platforms provide the resources necessary to run deep learning workloads including compute, storage, and networking. This means you no longer have to spend lots of money on expensive hardware and makes it easier for teams and researchers to deploy and train deep learning models faster. Cloud computing has ushered in a new era of deep learning developments by mobilizing the power of specialized hardware, notably GPUs, to accelerate the training and performance of deep learning models. 2025 IEEE. Subject The topic of the resource Artificial Intelligence; Cloud Computing; Deep Learning; Hardware; Infrastructure Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833156783-5; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online