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    AuthorAbdul Qudar, Mohiuddin Md (1)Aboulfotouh, Ahmed (1)As’ad, Anwar Munther (1)Bedda, Khaled (1)Chandrasekaran, Dhivya (1)Chow, Yik Lun (1)Das, Subrata (1)Deng, Haojin (1)Dingle, Liam (1)Elshafei, Mohamed (1)... View MoreSubjectMachine learning (7)Artificial Intelligence (AI) (3)Deep learning (3)Federated learning (2)Mobile edge computing (2)Natural language processing (2)Natural Language Processing (NLP) (2)5G networks (1)Academic mobility (1)AI (social media & healthcare) (1)... View MoreDate Issued2023 (20)2021 (15)2024 (8)2020 (7)2022 (6)Discipline
    Computer Science (56)

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    Exploration of contrastive learning strategies toward more robust stance detection systems 

    Rajendran, Udhaya Kumar (2023)
    Stance Detection, in general, is the task of identifying the author’s position on controversial topics. In Natural Language Processing, Stance Detection extracts the author’s attitude from the text written toward an issue ...
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    Texture classification on uneven surfaces using deep learning techniques 

    Marzani, Maliheh (2024)
    Robots are increasingly essential in various fields, excelling in tasks from routine operations to hazardous situations. Enhancing robots with human-like capabilities, such as tactile sensing, broadens their potential ...
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    Texture recognition from robotic tactile surface reconstruction: a reinforcement learning approach 

    Ramos Cheret, Laurent Yves Emile (2023)
    The ability to handle objects and recognize them and their properties by touch is a crucial ability that humans have. Thanks to tactile sensing, robots can do something similar by perceiving specific physical characteristics ...
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    Efficient routing algorithms in vehicular ad hoc networks 

    Ghaemi, Yashar (2021)
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    Toward lightweight fusion of AI logic and EEG sensors to enable ultra edge-based EEG analytics on IoT devices 

    Tazrin, Tahrat (2021)
    Electroencephalogram (EEG) analysis has garnered attention in the research domain due to its ability to detect various neural activities starting from brain seizures to a person’s concentration level. To make it more ...
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    Towards designing AI-aided lightweight solutions for key challenges in sensing, communication and computing layers of IoT: smart health use-cases 

    Sakib, Sadman (2021)
    The advent of the 5G and Beyond 5G (B5G) communication system, along with the proliferation of the Internet of Things (IoT) and Artificial Intelligence (AI), have started to evolve the vision of the smart world into a ...
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    Enhancing machine vision using human cognition from EEG analysis 

    Mishra, Alankrit (2022)
    Visual classification is the perceptible/computational effort of arranging objects and visual contexts into distinct labels. Humans and machines have mastered this advanced problem in their own varied contexts. However, ...
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    Permissioned blockchains for real world applications 

    Ismail, Ashiana (2020)
    Blockchain technology, even though relatively new, has evolved rapidly in the past 12 years. Bitcoin’s underlying technology - the first blockchain - was a public, permissionless, and completely decentralized network ...
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    Harnessing generative AI for overcoming labeled data challenges in social media NLP 

    Liyanage, Chandreen Ravihari (2023)
    With the introduction of Transformers and Large Language Models, the field of NLP has significantly evolved. Generative AI, a prominent transformer-based technology for crafting human-like content, has proven powerful ...
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    Lightweight deep learning for monocular depth estimation 

    Heydrich, Tim (2021)
    Monocular depth estimation is a challenging but significant part of computer vision with many applications in other areas of study. This estimation method aims to provide a relative depth prediction for a single input ...
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