Sardar Hasen Ali^*, Maiwan Bahjat Abdulrazzaq

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 429-448, 2024, DOI:10.32604/cmc.2024.048356

Abstract Handwritten character recognition (HCR) involves identifying characters in images, documents, and various sources such as forms surveys, questionnaires, and signatures, and transforming them into a machine-readable format for subsequent processing. Successfully recognizing complex and intricately shaped handwritten characters remains a significant obstacle. The use of convolutional neural network (CNN) in recent developments has notably advanced HCR, leveraging the ability to extract discriminative features from extensive sets of raw data. Because of the absence of pre-existing datasets in the Kurdish language, we created a Kurdish handwritten dataset called (KurdSet). The dataset consists of Kurdish characters, digits, texts, and symbols. The dataset… More >

Yuejie Li^1,2,*, Shijun Li³

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3041-3070, 2024, DOI:10.32604/cmc.2023.045741

Abstract 6G is envisioned as the next generation of wireless communication technology, promising unprecedented data speeds, ultra-low Latency, and ubiquitous Connectivity. In tandem with these advancements, blockchain technology is leveraged to enhance computer vision applications’ security, trustworthiness, and transparency. With the widespread use of mobile devices equipped with cameras, the ability to capture and recognize Chinese characters in natural scenes has become increasingly important. Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount, such as facial recognition or personal healthcare monitoring. Users can control their visual data and grant or revoke access as needed. Recognizing Chinese characters from images… More >

Haipeng Sun^1,2, Xueyan Ding^1,2,*, Jian Sun^1,2, Hua Yu³, Jianxin Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2721-2739, 2024, DOI:10.32604/cmc.2024.046449

Abstract Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition, we present a deep learning-based approach for Yi character detection and recognition. In the detection stage, an improved Differentiable Binarization Network (DBNet) framework is introduced to detect Yi characters, in which the Omni-dimensional Dynamic Convolution (ODConv) is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features, thereby improving the accuracy of Yi character detection. Then, the feature pyramid network fusion module is used to further extract Yi character image features, improving target recognition… More >

Arfa Siddiqu, Abdul Basit^*, Waheed Noor, Muhammad Asfandyar Khan, M. Saeed H. Kakar, Azam Khan

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 875-885, 2023, DOI:10.32604/iasc.2023.036426

Abstract The optical character recognition for the right to left and cursive languages such as Arabic is challenging and received little attention from researchers in the past compared to the other Latin languages. Moreover, the absence of a standard publicly available dataset for several low-resource languages, including the Pashto language remained a hurdle in the advancement of language processing. Realizing that, a clean dataset is the fundamental and core requirement of character recognition, this research begins with dataset generation and aims at a system capable of complete language understanding. Keeping in view the complete and full autonomous recognition of the cursive… More >

A. Naresh Kumar^1,*, G. Geetha²

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2619-2637, 2023, DOI:10.32604/iasc.2023.028349

Abstract Recognizing signs and fonts of prehistoric language is a fairly difficult job that requires special tools. This stipulation make the dispensation period overriding, difficult and tiresome to calculate. This paper present a technique for recognizing ancient south Indian languages by applying Artificial Neural Network (ANN) associated with Opposition based Grey Wolf Optimization Algorithm (OGWA). It identifies the prehistoric language, signs and fonts. It is an apparent from the ANN system that arbitrarily produced weights or neurons linking various layers play a significant role in its performance. For adaptively determining these weights, this paper applies various optimization algorithms such as Opposition… More >

Rujian Lan^1,2,3,#, Meiyang Duan^1,2,3,#, Feida Wu^1,2,3,#, Rifang Lai^1,2,3, Zhaowen Mo^1,2,3, Shenggang Pan^1,2,3, Xiangru Tang^1,2,3,*

Phyton-International Journal of Experimental Botany, Vol.91, No.11, pp. 2461-2473, 2022, DOI:10.32604/phyton.2022.021884

Abstract Fragrant rice is popular for the good grain quality and special aroma. The present study conducted a field experiment to investigate the effects of ultrasonic seed treatment on grain yield, quality characters, physiological properties and aroma biosynthesis of different fragrant rice genotypes. The seeds of three fragrant rice genotypes were exposed to 1 min of ultrasonic vibration and then cultivated in paddy field. The results of present study showed that ultrasonic seed treatment increased grain yield of all fragrant rice genotypes but the responses of yield formation to ultrasonic were varied with different genotypes. Compared with control, ultrasonic seed treatment increased… More >

Sagheer Abbas¹, Yousef Alhwaiti², Areej Fatima³, Muhammad A. Khan⁴, Muhammad Adnan Khan^5,*, Taher M. Ghazal^6,7, Asma Kanwal^1,8, Munir Ahmad¹, Nouh Sabri Elmitwally^2,9

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4563-4581, 2022, DOI:10.32604/cmc.2022.021102

Abstract This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy recognition results. The proposed system… More >

Gibrael Abosamra^*, Hadi Oqaibi

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1-28, 2021, DOI:10.32604/cmc.2021.015318

Abstract Even though much advancements have been achieved with regards to the recognition of handwritten characters, researchers still face difficulties with the handwritten character recognition problem, especially with the advent of new datasets like the Extended Modified National Institute of Standards and Technology dataset (EMNIST). The EMNIST dataset represents a challenge for both machine-learning and deep-learning techniques due to inter-class similarity and intra-class variability. Inter-class similarity exists because of the similarity between the shapes of certain characters in the dataset. The presence of intra-class variability is mainly due to different shapes written by different writers for the same character. In this… More >

Sulaiman Khan¹, Shah Nazir¹, Habib Ullah Khan^2,*, Anwar Hussain¹

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2831-2844, 2021, DOI:10.32604/cmc.2021.015054

Abstract During the last two decades significant work has been reported in the field of cursive language’s recognition especially, in the Arabic, the Urdu and the Persian languages. The unavailability of such work in the Pashto language is because of: the absence of a standard database and of significant research work that ultimately acts as a big barrier for the research community. The slight change in the Pashto characters’ shape is an additional challenge for researchers. This paper presents an efficient OCR system for the handwritten Pashto characters based on multi-class enabled support vector machine using manifold feature extraction techniques. These… More >

Zahoor Ahmad^1,2,*, Ejaz Ahmad Waraich³, Muhammad Zia ur Rehman⁴, Muhammad Ashar Ayub⁴, Muhammad Usman⁴, Hesham Alharby⁵, Atif Bamagoos⁵, Celaleddin Barutçular¹, Muhammad Ali Raza⁶, Fatih Çiğ⁷, Ayman El Sabagh^7,8,*

Phyton-International Journal of Experimental Botany, Vol.90, No.2, pp. 503-514, 2021, DOI:10.32604/phyton.2021.013588

Abstract Water is essential for the growth period of crops; however, water unavailability badly affects the growth and physiological attributes of crops, which considerably reduced the yield and yield components in crops. Therefore, a pot experiment was conducted to investigate the effect of foliar phosphorus (P) on morphological, gas exchange, biochemical traits, and phosphorus use efficiency (PUE) of maize (Zea mays L.) hybrids grown under normal as well as water deficit situations at the Department of Agronomy, University of Agriculture Faisalabad, Pakistan in 2014. Two different treatments (control and P @ 8 kg ha⁻¹ ) and four hybrids (Hycorn, 31P41, 65625,… More >