Titlebook: Intelligent Systems Design and Applications; Machine Learning Sol Ajith Abraham,Anu Bajaj,Thomas Hanne Conference proceedings 2024 The Edit

Hectic

Classification of Cardiac Arrhythmia Using Machine Learning Algorithms,ody and it is also considered to be the primary organ of our circulatory system. Arrhythmia is one of those common disorders which occur due to an irregular heartbeat and hence it is also known as heart rhythm problem which can be best detected with the help of Electrocardiogram (ECG). ECG is a test

参考书目

,Exploring Machine Learning Approaches for Precipitation Prediction: Post Processing of Daily Accumusts. Leveraging an extensive North American dataset that includes precipitation data sourced from Numeric Weather Prediction models from various Canadian, American, and European weather agencies. In our approach, we integrate meteorological attributes such as cloud cover, wind patterns, geographical

apropos

合适

,A Layout Independent Deep Learning Framework for Recognition of Courtesy-Amount in Bank-Cheque Imagut specific analysis of the cheque template. The proposed framework employs a refined Mask-RCNN-based segmentation module to localize the courtesy amount in the bank cheque and subsequently, extract the digits of the segmented courtesy field region. The sequence of the extracted digits is further pr

挑剔为人

Convolutional Neural Network (CNN) Classifiers Used in Land Use/Land Cover Monitoring and Classific Utilization and to take the right decisions to protect the environment. This article discusses various techniques/algorithms used to build robust models to perform Land Use/Land Cover Classification. The article includes various architecture models including Convolutional Neural Networks (CNN), Rec

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捐助

Analysis of Deepfake Attacks and Detection Techniques in Smart City Applications,dy aims to provide valuable insights into countering deepfake threats within the smart city landscape, ensuring the continued trustworthiness of critical systems and data. This paper presents a comprehensive analysis of deepfake attacks and explores state-of-the-art detection techniques that can saf

易碎

Deep-Net: Brain Lesion Segmentation with 3D CNN and Residual Connections,nt monitoring, and facilitate comprehensive studies of pathology on a large scale. This innovative approach not only enhances the efficiency of the model but also exhibits significant promise for segmentation tasks, particularly within the realm of medical imaging. Leveraging the residual connection

NIL

A Bimodal Autism Spectrum Disorder Detection Using fMRI Images,ilize neuroimaging data to enhance diagnostic accuracy and clinical applicability. Particularly, functional Magnetic Resonance Imaging (fMRI) data are explored as input for the proposed machine learning based solutions. However, from fMRI, several brain atlases are provided to describe functional co

Fissure

,Brood Parasitism Identification Using a Deep Learning Model with Mish Activation Function,o crack the eggs, which is a destructive process. The host female leaves the nest when she discovers a parasite egg there. Due to this behavior, an important number of future birds disappear and the behavior is extended. Indeed, the cuckoo is one of the species responding to the brood parasitism. Ad