Mustafa M. Al Rifaee^1,*, Mohammad M. Abdallah¹, Mosa I. Salah², Ayman M. Abdalla¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5063-5073, 2022, DOI:10.32604/cmc.2022.030033

Abstract Hand veins can be used effectively in biometric recognition since they are internal organs that, in contrast to fingerprints, are robust under external environment effects such as dirt and paper cuts. Moreover, they form a complex rich shape that is unique, even in identical twins, and allows a high degree of freedom. However, most currently employed hand-based biometric systems rely on hand-touch devices to capture images with the desired quality. Since the start of the COVID-19 pandemic, most hand-based biometric systems have become undesirable due to their possible impact on the spread of the pandemic. Consequently, new contactless hand-based biometric… More >

Ng Lai Yee¹, Mohd Asyraf Zulkifley^2,*, Adhi Harmoko Saputro³, Siti Raihanah Abdani⁴

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5331-5348, 2022, DOI:10.32604/cmc.2022.028801

Abstract Micro-expression is manifested through subtle and brief facial movements that relay the genuine person’s hidden emotion. In a sequence of videos, there is a frame that captures the maximum facial differences, which is called the apex frame. Therefore, apex frame spotting is a crucial sub-module in a micro-expression recognition system. However, this spotting task is very challenging due to the characteristics of micro-expression that occurs in a short duration with low-intensity muscle movements. Moreover, most of the existing automated works face difficulties in differentiating micro-expressions from other facial movements. Therefore, this paper presents a deep learning model with an attention… More >

Sana Yasin¹, Umar Draz^2,3,*, Tariq Ali⁴, Kashaf Shahid¹, Amna Abid¹, Rukhsana Bibi¹, Muhammad Irfan⁵, Mohammed A. Huneif⁶, Sultan A. Almedhesh⁶, Seham M. Alqahtani⁶, Alqahtani Abdulwahab⁶, Mohammed Jamaan Alzahrani⁶, Dhafer Batti Alshehri⁶, Alshehri Ali Abdullah⁷, Saifur Rahman⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4349-4367, 2022, DOI:10.32604/cmc.2022.028251

Abstract Diagnosing a baby’s feelings poses a challenge for both doctors and parents because babies cannot explain their feelings through expression or speech. Understanding the emotions of babies and their associated expressions during different sensations such as hunger, pain, etc., is a complicated task. In infancy, all communication and feelings are propagated through cry-speech, which is a natural phenomenon. Several clinical methods can be used to diagnose a baby’s diseases, but nonclinical methods of diagnosing a baby’s feelings are lacking. As such, in this study, we aimed to identify babies’ feelings and emotions through their cry using a nonclinical method. Changes… More >

Sankar Sennan¹, Digvijay Pandey^2,*, Youseef Alotaibi³, Saleh Alghamdi⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 343-361, 2022, DOI:10.32604/cmc.2022.028334

Abstract In the present scenario, Deep Learning (DL) is one of the most popular research algorithms to increase the accuracy of data analysis. Due to intra-class differences and inter-class variation, image classification is one of the most difficult jobs in image processing. Plant or spinach recognition or classification is one of the deep learning applications through its leaf. Spinach is more critical for human skin, bone, and hair, etc. It provides vitamins, iron, minerals, and protein. It is beneficial for diet and is readily available in people's surroundings. Many researchers have proposed various machine learning and deep learning algorithms to classify… More >

Muhammad Jamil Hussain¹, Ahmad Shaoor¹, Suliman A. Alsuhibany², Yazeed Yasin Ghadi³, Tamara al Shloul⁴, Ahmad Jalal¹, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5327-5343, 2022, DOI:10.32604/cmc.2022.025953

Abstract In this research work, an efficient sign language recognition tool for e-learning has been proposed with a new type of feature set based on angle and lines. This feature set has the ability to increase the overall performance of machine learning algorithms in an efficient way. The hand gesture recognition based on these features has been implemented for usage in real-time. The feature set used hand landmarks, which were generated using media-pipe (MediaPipe) and open computer vision (openCV) on each frame of the incoming video. The overall algorithm has been tested on two well-known ASL-alphabet (American Sign Language) and ISL-HS… More >

Anil Kumar Yadav¹, R. K. Pateriya², Nirmal Kumar Gupta³, Punit Gupta^4,*, Dinesh Kumar Saini⁴, Mohammad Alahmadi⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2697-2712, 2022, DOI:10.32604/cmc.2022.023052

Abstract Face recognition systems have enhanced human-computer interactions in the last ten years. However, the literature reveals that current techniques used for identifying or verifying faces are not immune to limitations. Principal Component Analysis-Support Vector Machine (PCA-SVM) and Principal Component Analysis-Artificial Neural Network (PCA-ANN) are among the relatively recent and powerful face analysis techniques. Compared to PCA-ANN, PCA-SVM has demonstrated generalization capabilities in many tasks, including the ability to recognize objects with small or large data samples. Apart from requiring a minimal number of parameters in face detection, PCA-SVM minimizes generalization errors and avoids overfitting problems better than PCA-ANN. PCA-SVM, however,… More >

Jae Myung Kim^1,2, Gyu Ho Choi², Min-Gu Kim², Sung Bum Pan^1,2,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1213-1227, 2022, DOI:10.32604/cmc.2022.025213

Abstract Recently, user recognition methods to authenticate personal identity has attracted significant attention especially with increased availability of various internet of things (IoT) services through fifth-generation technology (5G) based mobile devices. The EMG signals generated inside the body with unique individual characteristics are being studied as a part of next-generation user recognition methods. However, there is a limitation when applying EMG signals to user recognition systems as the same operation needs to be repeated while maintaining a constant strength of muscle over time. Hence, it is necessary to conduct research on multidimensional feature transformation that includes changes in frequency features over… More >

K. Babu^1,*, C. Kumar², C. Kannaiyaraju³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756

Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component analysis-based dimensionality reduction techniques are… More >

K. O. Mohammed Aarif^1,*, P. Sivakumar²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 275-289, 2022, DOI:10.32604/iasc.2022.022805

Abstract Deep learning has achieved magnificent success in the field of pattern recognition. In recent years Urdu character recognition system has significantly benefited from the effectiveness of the deep convolutional neural network. Majority of the research on Urdu text recognition are concentrated on formal handwritten and printed Urdu text document. In this paper, we experimented the Challenging issue of text recognition in Urdu ancient literature documents. Due to its cursiveness, complex word formation (ligatures), and context-sensitivity, and inadequate benchmark dataset, recognition of Urdu text from the literature document is very difficult to process compared to the formal Urdu text document. In… More >

Parneet Kaur¹, Yogesh Kumar¹, Shakeel Ahmed^2,*, Abdulaziz Alhumam², Ruchi Singla³, Muhammad Fazal Ijaz⁴

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 35-50, 2022, DOI:10.32604/cmc.2022.017681

Abstract Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with regard to unusual varieties… More >