Titlebook: Information and Communication Technology and Applications; Third International Sanjay Misra,Bilkisu Muhammad-Bello Conference proceedings

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Ojuh O. Divine,Isabona Josephive data obtained through in-depth interviews. The research describes a recent study examining the impact of enterprise education on students pursuing Professional Higher Education (PHE) at an extensive vocational educational institution in the EU state of Malta. This paper aims to demonstrate how M

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Benjamin A. Gyunka,Oluwakemi C. Abikoye,Adekeye S. Adekunleor two cameras to measure 2D or 3D dynamics. The frames of the recorded videos are then postprocessed to correlate the structure points at different times and obtain displacement information. A plethora of cameras is available—in terms of frame rate, resolution, versatility, and overall quality—the

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Kayode Omotosho Alabi,Sulaiman Olaniyi Abdulsalam,Roseline Oluwaseun Ogundokun,Micheal Olaolu Arowolipulation of ECG signals can result in inaccurate diagnosis or treatment because these signals are crucial for identifying and monitoring cardiovascular illnesses. Also, these signals are frequently sent via the internet, raising the possibility of unwanted access and manipulation. Hence, ECG signal

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Adam Adenike Azeezat,Onashoga Sadiat Adebukola,Abayomi-Alli Adebayo,Omoyiola Bayo Olusholaworks. Nonetheless, the growing complexity of datasets and the ongoing pursuit of enhanced performance necessitate innovative approaches. In this study, we introduce a novel deep neural network, referred to as the “T-Fusion Net,” which incorporates multiple spatial attention mechanisms based on loca

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Ochilbek RakhmanovoV) in thermal imaging systems often results in insufficient and fragmented large Field of View (FoV) simulation data, thereby compromising the effectiveness of defense applications using large Field of View (FoV) cameras. To address this challenge, we propose an innovative approach employing image

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Emmanuel Adetiba,Amarachi E. Opara,Oluwaseun T. Ajayi,Folashade O. Owolabien contains excessive noise, whereas radar point clouds retain only limited information. In this work, we holistically treat the sparse nature of radar data by introducing an adaptive subsampling method together with a tailored network architecture that exploits the sparsity patterns to discover glo

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Usman Haruna,Umar Sunusi Maitalata,Murtala Mohammed,Jaafar Zubairu Maitamamethods modify softmax scores fine-tuned on outlier data or leverage intermediate feature layers to identify distinctive patterns between In-Distribution (ID) and OOD samples. Other methods focus on employing diverse OOD samples to learn discrepancies between ID and OOD. These techniques, however, a

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https://doi.org/10.1007/978-3-030-69143-1artificial intelligence; communication channels (information theory); communication systems; computer h

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