This paper revolves around weapon recognition. It introduces the dual-framework dispute of
the target to control two CNNs that are used to foreground jointly with the SVM-P and fuse …

This research presents a new use of Convolutional Neural Networks (CNN) integrated with
Federated Learning (FL) for detecting and classifying illnesses on sunflower leaves. The …

PD, or Parkinson's Disease, is a neurodegenerative disorder that commonly disorients
movement abilities. Hence, correctly identifying this disease at its early stages is essential …

The report presents a detailed methodology involving convolutional neural networks (CNN)
and support vector machines (SVM), which are used to label predefined cricket bowling …

This study tries to marry Convolutional Neural Networks (CNN) and Support Vector Machine
(SVN) techniques to form a very advanced gun identification system. The system's unique …

The created algorithm was assessed rigorously, employing numerous performance metrics
that were calculated per the categories of skin lesion detection. The precision for each class …

To obtain a metric precision of 88.33% and a metric recall of 87.13%, the Fl-Score being
87.72%. The data shows three classes separated as Class 1, which occupies 20% of the …

In this study, the point where machine learning combines Convolutional Neural Networks
(CNN) and Random Forest (RF) models help to identify Parkinson's Disease (PD) in a very …

This paper encompasses meaningful discussions of affect recognition algorithms and a
heterogeneous architecture that merges SVMs with CNNs. The model was mainly created …

This article proposes a thorough research study between federated learning and CNNs,
where both methods are utilized for the detection and severity categorization of broccoli leaf …