Pub Date : 2023-09-30DOI: 10.47363/jaicc/2023(2)128
Suresh Babu Rajasekaran
Computer vision and language AI (or speech AI) are two rapidly growing fields that have the potential to revolutionize the way when interacted with technology. When it comes to artificial intelligence, there are two main branches: computer vision, which focuses on visual data, and language AI (or voice AI), which focuses on both written and spoken language. The purpose of this research is to offer a snapshot of where things stand in this area right now, highlighting recent research and key findings in both computer vision and language AI (or speech AI). The literature review will focus on the most recent advancements and trends in these fields, as well as identify gaps in the literature that need further research.
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Pub Date : 2023-09-30DOI: 10.47363/jaicc/2023(2)131
Suresh Babu Rajasekaran
This comprehensive literature review examines the latest breakthroughs in computer vision and natural language processing (NLP), two rapidly evolving fields with applications across search, human-computer interaction, robotics, and more. It synthesizes key findings, trends, limitations, and open challenges from cutting-edge research at their intersection. The dramatic progress driven by deep neural networks is analysed in depth, along with issues like generalization, context handling, reasoning, uncertainty, and human-centric evaluation. Although remarkable advances have been made, especially in computer vision, core problems remain to be addressed. This review provides a thorough overview of the state-of-the-art, reflecting the most recent innovations, and promising future directions in this dynamic research domain.
{"title":"Literature Review: Recent Advances in Computer Vision and Language AI","authors":"Suresh Babu Rajasekaran","doi":"10.47363/jaicc/2023(2)131","DOIUrl":"https://doi.org/10.47363/jaicc/2023(2)131","url":null,"abstract":"This comprehensive literature review examines the latest breakthroughs in computer vision and natural language processing (NLP), two rapidly evolving fields with applications across search, human-computer interaction, robotics, and more. It synthesizes key findings, trends, limitations, and open challenges from cutting-edge research at their intersection. The dramatic progress driven by deep neural networks is analysed in depth, along with issues like generalization, context handling, reasoning, uncertainty, and human-centric evaluation. Although remarkable advances have been made, especially in computer vision, core problems remain to be addressed. This review provides a thorough overview of the state-of-the-art, reflecting the most recent innovations, and promising future directions in this dynamic research domain.","PeriodicalId":475827,"journal":{"name":"Journal of Artificial Intelligence & Cloud Computing","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135131235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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