Abdullah Ahmed Al-Dulaimi^1,*, Muhammet Tahir Guneser¹, Alaa Ali Hameed², Mohammad Shukri Salman³

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2291-2319, 2023, DOI:10.32604/cmes.2023.026065

Abstract Recently, the demand for renewable energy has increased due to its environmental and economic needs. Solar panels are the mainstay for dealing with solar energy and converting it into another form of usable energy. Solar panels work under suitable climatic conditions that allow the light photons to access the solar cells, as any blocking of sunlight on these cells causes a halt in the panels work and restricts the carry of these photons. Thus, the panels are unable to work under these conditions. A layer of snow forms on the solar panels due to snowfall in areas with low temperatures.… More > Graphic Abstract

S. Rajalakshmi^1,*, S. Nalini², Ahmed Alkhayyat³, Rami Q. Malik⁴

Computer Systems Science and Engineering, Vol.46, No.2, pp. 1673-1688, 2023, DOI:10.32604/csse.2023.034414

Abstract Remote sensing image (RSI) classifier roles a vital play in earth observation technology utilizing Remote sensing (RS) data are extremely exploited from both military and civil fields. More recently, as novel DL approaches develop, techniques for RSI classifiers with DL have attained important breakthroughs, providing a new opportunity for the research and development of RSI classifiers. This study introduces an Improved Slime Mould Optimization with a graph convolutional network for the hyperspectral remote sensing image classification (ISMOGCN-HRSC) model. The ISMOGCN-HRSC model majorly concentrates on identifying and classifying distinct kinds of RSIs. In the presented ISMOGCN-HRSC model, the synergic deep learning… More >

Swagata Boruah¹, Archit Dehloo¹, Prajul Gupta², Manas Ranjan Prusty^3,*, A. Balasundaram³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 927-942, 2023, DOI:10.32604/cmc.2023.035143

Abstract Diabetic Retinopathy (DR) is a serious hazard that can result in irreversible blindness if not addressed in a timely manner. Hence, numerous techniques have been proposed for the accurate and timely detection of this disease. Out of these, Deep Learning (DL) and Computer Vision (CV) methods for multiclass categorization of color fundus images diagnosed with Diabetic Retinopathy have sparked considerable attention. In this paper, we attempt to develop an extended ResNet152V2 architecture-based Deep Learning model, named ResNet2.0 to aid the timely detection of DR. The APTOS-2019 dataset was used to train the model. This consists of 3662 fundus images belonging… More >

Mohammad Yamin¹, Abdullah M. Basahel¹, Mona Abusurrah², Sulafah M Basahel³, Sachi Nandan Mohanty⁴, E. Laxmi Lydia^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 409-425, 2023, DOI:10.32604/cmc.2023.032432

Abstract White blood cells (WBC) or leukocytes are a vital component of the blood which forms the immune system, which is accountable to fight foreign elements. The WBC images can be exposed to different data analysis approaches which categorize different kinds of WBC. Conventionally, laboratory tests are carried out to determine the kind of WBC which is erroneous and time consuming. Recently, deep learning (DL) models can be employed for automated investigation of WBC images in short duration. Therefore, this paper introduces an Aquila Optimizer with Transfer Learning based Automated White Blood Cells Classification (AOTL-WBCC) technique. The presented AOTL-WBCC model executes… More >

Abdullah M. Basahel¹, Mohammad Yamin¹, Sulafah M. Basahel², Mona M. Abusurrah³, K.Vijaya Kumar⁴, E. Laxmi Lydia^5,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 133-148, 2023, DOI:10.32604/cmc.2023.031786

Abstract Osteosarcoma is one of the rare bone cancers that affect the individuals aged between 10 and 30 and it incurs high death rate. Early diagnosis of osteosarcoma is essential to improve the survivability rate and treatment protocols. Traditional physical examination procedure is not only a time-consuming process, but it also primarily relies upon the expert’s knowledge. In this background, the recently developed Deep Learning (DL) models can be applied to perform decision making. At the same time, hyperparameter optimization of DL models also plays an important role in influencing overall classification performance. The current study introduces a novel Symbiotic Organisms… More >

Rong-Guey Chang, Tam-Van Hoang^*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 999-1019, 2023, DOI:10.32604/csse.2023.034672

Abstract The diversity of software and hardware forces programmers to spend a great deal of time optimizing their source code, which often requires specific treatment for each platform. The problem becomes critical on embedded devices, where computational and memory resources are strictly constrained. Compilers play an essential role in deploying source code on a target device through the backend. In this work, a novel backend for the Open Neural Network Compiler (ONNC) is proposed, which exploits machine learning to optimize code for the ARM Cortex-M device. The backend requires minimal changes to Open Neural Network Exchange (ONNX) models. Several novel optimization… More >

P. S. Ramapraba^1,*, P. Epsiba², K. Umapathy³, E. Sivanantham⁴

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2177-2189, 2023, DOI:10.32604/iasc.2023.032040

Abstract The classification of lung nodules is a challenging problem as the visual analysis of the nodules and non-nodules revealed homogenous textural patterns. In this work, an Auxiliary Classifier (AC)-Generative Adversarial Network (GAN) based Lung Cancer Classification (LCC) system is developed. The proposed AC-GAN-LCC system consists of three modules; preprocessing, Lungs Region Detection (LRD), and AC-GAN classification. A Wiener filter is employed in the preprocessing module to remove the Gaussian noise. In the LRD module, only the lung regions (left and right lungs) are detected using iterative thresholding and morphological operations. In order to extract the lung region only, flood filling… More >

S. Poornima^1,*, N. Sripriya¹, Adel Fahad Alrasheedi², S. S. Askar², Mohamed Abouhawwash^3,4

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2393-2409, 2023, DOI:10.32604/iasc.2023.024820

Abstract Plant diseases prediction is the essential technique to prevent the yield loss and gain high production of agricultural products. The monitoring of plant health continuously and detecting the diseases is a significant for sustainable agriculture. Manual system to monitor the diseases in plant is time consuming and report a lot of errors. There is high demand for technology to detect the plant diseases automatically. Recently image processing approach and deep learning approach are highly invited in detection of plant diseases. The diseases like late blight, bacterial spots, spots on Septoria leaf and yellow leaf curved are widely found in plants.… More >

Huaxiang Song^*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5741-5756, 2023, DOI:10.32604/cmc.2023.034921

Abstract Over the past decade, the significant growth of the convolutional neural network (CNN) based on deep learning (DL) approaches has greatly improved the machine learning (ML) algorithm’s performance on the semantic scene classification (SSC) of remote sensing images (RSI). However, the unbalanced attention to classification accuracy and efficiency has made the superiority of DL-based algorithms, e.g., automation and simplicity, partially lost. Traditional ML strategies (e.g., the handcrafted features or indicators) and accuracy-aimed strategies with a high trade-off (e.g., the multi-stage CNNs and ensemble of multi-CNNs) are widely used without any training efficiency optimization involved, which may result in suboptimal performance.… More >

Pavitra Vasudevan¹, R. Faerie Mattins¹, S. Srivarshan¹, Ashvath Narayanan¹, Gayatri Wadhwani¹, R. Parvathi¹, R. Maheswari^2,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6039-6063, 2023, DOI:10.32604/cmc.2023.032331

Abstract Gait refers to a person’s particular movements and stance while moving around. Although each person’s gait is unique and made up of a variety of tiny limb orientations and body positions, they all have common characteristics that help to define normalcy. Swiftly identifying such characteristics that are difficult to spot by the naked eye, can help in monitoring the elderly who require constant care and support. Analyzing silhouettes is the easiest way to assess and make any necessary adjustments for a smooth gait. It also becomes an important aspect of decision-making while analyzing and monitoring the progress of a patient… More >