Abstract The vision transformer (ViT) architecture, with its attention mechanism based on multi-head layers, has been widely adopted in various computer-aided diagnosis tasks due to effectiveness processing medical image information. ViTs are notably recognized for their complex which requires high-performance GPUs or CPUs efficient model training and deployment real-world diagnostic devices. This renders them more intricate than convolutional neural networks (CNNs). difficulty is also...

Abstract Over the past two decades, several studies have paid great attention to biometric palmprint recognition. Recently, most methods in literature adopted deep learning due their high recognition accuracy and capability adapt with different acquisition images. However, high-dimensional data a large number of uncorrelated redundant features remain challenge computational complexity issues. Feature selection is process selecting subset relevant features, which aims decrease dimensionality,...

Currently, face recognition technology is the most widely used method for verifying an individual's identity. Nevertheless, it has increased in popularity, raising concerns about presentation attacks, which a photo or video of authorized person's to obtain access services. Based on combination background subtraction (BS) and convolutional neural network(s) (CNN), as well ensemble classifiers, we propose efficient more robust attack detection algorithm. This algorithm includes fully connected...

Breast cancer is a significant global health concern, highlighting the critical importance of early detection for effective treatment women’s health. While convolutional networks (CNNs) have been best analysing medical images, recent interest has emerged in leveraging vision transformers (ViTs) data analysis. This study aimed to conduct comprehensive comparison three systems self-attention transformer (VIT), compact convolution (CCT), and tokenlearner (TVIT) binary classification mammography...

Person's identity validation is becoming much more essential due to the increasing demand for high-security systems. A biometric system testifies authenticity of specific physiological or behavioral characteristics-based technology. This technology has been successfully applied verification and identification We analyze multispectral palmprint in unimodal multimodal modes. In an system, feature extraction a crucial step. For this reason, we propose efficient deep learning algorithm called...

Clustering is inherently a process of exploratory data analysis. It has attracted more attention recently because much real-world consists multiple representations or views. However, it becomes increasingly problematic when dealing with large and heterogeneous data. worth noting that several approaches have been developed to increase computational efficiency, although most them some drawbacks: 1) Most existing techniques consider equal static weights quantify importance across different...

In the last years, several researchers have interested in two-dimensional (2D) palmprint recognition. order to enhance security of biometric systems, recently, some works proposed use three-dimensional (3D) The advantage using 3D capture systems is that they 2D and at same time, give different complementary information. component contains depth palm surface, whereas texture. this paper, we an efficient identification system combining by fusing them matching score level. To exploit data,...

Biometric technology has become essential in our daily life. In such a biometric system, personal identification is based on behavioral or biological characteristics. Recently, the trait of Finger-Knuckle-Print (FKP) used due to its ease use and low cost. order develop an efficient recognition system these images, we propose deep learning method where own Convolutional Neural Network (CNN) identify persons. Excellent results were conducted with unimodal multimodal systems.

Currently, face recognition technologies are the most widely used methods for verifying 1an individual’s identity. Nevertheless, it has increased in popularity, raising concerns about spoofing attacks, which a photo or video of an authorized person’s is to get access services. Based on combination Background Subtraction (BS) and Convolutional Neural Networks (CNN), as well ensemble classifiers, we propose efficient more robust spoof detection algorithm. This algorithm...

Due to security imperatives, biometrics has attracted a lot of attention in recent decades. Biometric recognition refers the identification individuals based on their physiological and/or behavioral traits. Among various traits, palmprint modality, which contains rich biometric features, become one essential features that prove effectiveness improving system accuracy. In addition texture infrared light can capture vein-net palm, an independent trait called palm-vein. Fortunately, these two...

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In nearest past years object detection techniques becomes the magic key to solving several problems in computer vision, this work, we introduce our enhanced YOLO v5 detector for detecting SNCF (National Society of France Railroad) workers railway environment. Our contribution work is presented by creating a new dataset about use training model and improving reducing number its parameters where reduce classes layers only one class, that ensure augment speed increase accuracy detector....

The detection of the novel coronavirus disease (COVID-19) has recently become a critical task for medical diagnosis. Knowing that deep Learning is an advanced area machine learning gained much interest, especially convolutional neural network. It been widely used in variety applications. Since it proved transfer effective classification tasks, this study; COVID -19 system implemented as quick alternative, accurate and reliable diagnosis option to detect COVID-19 disease. Three pre-trained...

Over the past two decades, there has been an explosion of biometric technologies because anything that characterizes a person provides source information. The palmprint modality is characteristic great interest to researchers, and its traits can be found in variety representations, including grayscale, color, multi/hyperspectral representations. most difficult challenge developing hyperspectral palmprint-based recognition system determining how use all information available these spectral...

Secure personal identification remains a paramount challenge in contemporary society, necessitating robust and reliable identity verification mechanisms. Biometric systems offer promising avenue, given their inherent secu-rity attributes. In particular, the finger knuckle print (FKP) vein (FV) are emerging as potent hand biometric modalities. this paper, we employed convolutional neural networks (CNNs), foundational structures deep learning, owing to unparalleled proficiency image analysis....