Titlebook: ICT for Intelligent Systems; Proceedings of ICTIS Jyoti Choudrie,Parikshit N Mahalle,Amit Joshi Conference proceedings 2024 The Editor(s) (

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,Object Tracking System on Zynq UltraScale+ MPSoC ZCU104, supervised real-time (CSRT), MOSSE, and more, implemented on the Zynq UltraScale+ Multiprocessor System on Chip (MPSoC) ZCU104 platform. Single object tracking is a critical task in computer vision and robotics, enabling the real-time monitoring and analysis of moving objects in various application

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,Real-Time Multi-object Detection and Tracking on Zynq UltraScale+ MPSoc,ation technologies. This paper introduces a holistic approach to multi-object tracking implemented on a Zynq UltraScale+ MPSoc ZCU104 Evaluation Kit. The proposed system harnesses the YOLOv8 object detection model from Ultralytics for robust and efficient object detection. Additionally, it integrate

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Enhanced Object Detection and Segmentation in Satellite Imagery Through Modified Convolutional Netwvision algorithms are needed to effectively retrieve pertinent data from these massive databases. In this work, we use enhanced convolutional neural networks along with transfer learning algorithms to present a unique method for object recognition and categorization in satellite data. By utilizing d

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Machine Learning-Based Hybrid Precoding for Next-Generation Wireless Communication Systems: A Comprltiple-output (MIMO) technology, particularly in millimeter wave (mmWave) and beyond-5G systems. Hybrid precoding, a technique that combines digital and analog precoding, has emerged as a critical enabler for achieving the massive antenna arrays required for these systems while maintaining energy ef

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An Exploratory Analysis of Deep Learning Models for Detection of Lung Cancer in Medical Images,d investigation and comparative analysis of four models in deep learning (Extreme Learning Machine (ELM), VGG16, ResNet50, and VGG19) applied to the important task of detecting lung cancer from medical images. The goal of the project is to gain nuanced insights into the trade-offs between model comp

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