In this paper we explore a new model focused on integrating two classifiers; Convolutional Neural Network (CNN) and Support Vector Machine (SVM) for offline Arabic handwriting recognition (OAHR) which the dropout technique was applied. The suggested system altered trainable classifier of CNN by SVM classifier. A convolutional network is beneficial extracting features information functions as recognizer. It found that both automatically extracts from raw images performs classification....

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...

The diagnosis of the plants is carried out with a visual inspection by experts and biological examination second choice if necessary. They are usually expensive time consuming. This inspired several computer methodologies to detect plant blights based on their leaf images. We apply methodology Deep Learning systems artificial neural networks, this branch also allows for early detection diseases, applying convolutional networks (CNNs) familiar some famous architectures, notably "ResNet"...

Hand gestures are natural and intuitive communication way for the human being to interact with his environment. They serve designate or manipulate objects, enhance speech, communicate in a noisy place. can also be separate language. Gestures have different meanings according language culture. machines. The subject of our research concerns design development computer vision methods recognizing hand by mobile device. We proposed system based on SVM various gestures. consists four steps:...

In the handwriting recognition field, deep learning is becoming new trend thanks to their ability deal with unlabeled raw data especially huge size of available nowadays. this paper, we investigate Deep Belief Neural Network (DBNN) for Arabic handwritten character/word recognition. The proposed system takes as input and proceeds a grasping layer-wise unsupervised algorithm. approach was tested on two different databases. For character level one, results were promising an error classification...

Since the mid 2010's, Deep learning has been regarded as a boom and consequently it big success in large field of applications like speech pattern recognition. Handwriting recognition is indeed amongst triumphal Despite being quite matured, this still ambiguous for Arabic handwritten script hence several questions are challenge. In study, Belief Network (DBN) investigated. We then ensure DBN architecture against over-fitting because mighty performance dropout dropconnect. Training with both...

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...

Deep learning algorithms, as a machine algorithms developed in recent years, have been successfully applied various domains of computer vision, such face recognition, object detection and image classification. These aim at extracting high representation the data via multi-layers deep hierarchical structure. However, to authors' knowledge, these approaches not extensively studied recognize Arabic Handwritten Script (AHS). In this paper, they present model based on Support Vector Machine (SVM)...

Handwriting recognition ranks among the highest and most triumphant applications in pattern domain. Despite being a developed field, many enquiries are still needed represent defiance mainly for Arabic Handwritten Script (AHS). Recently, more regard has been given to Support Vector Machines (SVM) classifier script recognition. Nevertheless, it not put application yet handwritten field if compared with other methods like ANN, CNN, RNN HMM. SVMs AHS is examined this paper. Handcrafted feature...

Convolutional neural network (CNN), as a deep learning algorithms being developed for years, have been successfully applied in various domains of computer vision and pattern recognition. Recently, support vector machine (SVM) classifier has received more attention script In this paper, we investigated new model based on the integration two classifiers which are CNN SVM methods offline Arabic handwriting The proposed system modified trainable by classifier. CNN-based aims at extracting an...

As a machine learning algorithms, deep algorithms developed in recent years, have been successfully practiced many fields of computer vision, like face recognition, object detection and image classification. These Deep look for drawing out very performing representation the data, among which speech, through multi-layers hierarchical structure. In this study, model based on Support Vector Machine (SVM) named SVM (DSVM) is represented. We applied dropout technique (DSVM). It worth noting that...

In recent years, deep learning (DL) based systems have become very popular for constructing hierarchical representations from unlabeled data. Moreover, DL approaches been shown to exceed foregoing state of the art machine models in various areas, by pattern recognition being one more important cases. This paper applies Convolutional Deep Belief Networks (CDBN) textual image data containing Arabic handwritten script (AHS) and evaluated it on two different databases characterized...

Recently, personal identification, which is based on the palmprint texture features analysis, has widely attracted attention of several researchers and gained a great popularity in pattern recognition field. In this paper, we present novel methodology information extracted from palmprint. Firstly, propose an algorithm to robustly locate Region Of Interest (ROI) hand. Secondly, combine multiple descriptors extract information, are Gray-Level Co-occurrence Matrix (GLCM) Gabor filters using...