Pawat Chunhachatrachai^1,*, Chyi-Yeu Lin^1,2

Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 599-618, 2024, DOI:10.32604/iasc.2024.055385 - 06 September 2024

Abstract Angle detection is a crucial aspect of industrial automation, ensuring precise alignment and orientation of components in manufacturing processes. Despite the widespread application of computer vision in industrial settings, angle detection remains an underexplored domain, with limited integration into production lines. This paper addresses the need for automated angle detection in industrial environments by presenting a methodology that eliminates training time and higher computation cost on Graphics Processing Unit (GPU) from machine learning in computer vision (e.g., Convolutional Neural Networks (CNN)). Our approach leverages advanced image processing techniques and a strategic combination of algorithms, including More >

Narayanan Ganesh¹, Rajendran Shankar², Miroslav Mahdal³, Janakiraman Senthil Murugan⁴, Jasgurpreet Singh Chohan⁵, Kanak Kalita^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 103-141, 2024, DOI:10.32604/cmes.2023.028018 - 30 December 2023

Abstract Computer vision (CV) was developed for computers and other systems to act or make recommendations based on visual inputs, such as digital photos, movies, and other media. Deep learning (DL) methods are more successful than other traditional machine learning (ML) methods in CV. DL techniques can produce state-of-the-art results for difficult CV problems like picture categorization, object detection, and face recognition. In this review, a structured discussion on the history, methods, and applications of DL methods to CV problems is presented. The sector-wise presentation of applications in this paper may be particularly useful for researchers More >

Yonghun Jang, Yeong-Seok Seo^*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2247-2263, 2023, DOI:10.32604/cmc.2023.027882 - 06 February 2023

Abstract Food processing companies pursue the distribution of ingredients that were packaged according to a certain weight. Particularly, foods like fish are highly demanded and supplied. However, despite the high quantity of fish to be supplied, most seafood processing companies have yet to install automation equipment. Such absence of automation equipment for seafood processing incurs a considerable cost regarding labor force, economy, and time. Moreover, workers responsible for fish processing are exposed to risks because fish processing tasks require the use of dangerous tools, such as power saws or knives. To solve these problems observed in… More >

Abdul Wahab Hashmi¹, Harlal Singh Mali¹, Anoj Meena¹, Mohammad Farukh Hashmi², Neeraj Dhanraj Bokde^3,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 917-1005, 2023, DOI:10.32604/cmes.2023.021223 - 27 October 2022

Abstract Computer vision provides image-based solutions to inspect and investigate the quality of the surface to be measured. For any components to execute their intended functions and operations, surface quality is considered equally significant to dimensional quality. Surface Roughness (Ra) is a widely recognized measure to evaluate and investigate the surface quality of machined parts. Various conventional methods and approaches to measure the surface roughness are not feasible and appropriate in industries claiming 100% inspection and examination because of the time and efforts involved in performing the measurement. However, Machine vision has emerged as the innovative More >

R. Ganesan^1,*, G. Sankaranarayanan¹, M. Pradeep Kumar², V. K. Bupesh Raja¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 667-681, 2023, DOI:10.32604/iasc.2023.031932 - 29 September 2022

Abstract This research introduces a challenge in integrating and cleaning the data, which is a crucial task in object matching. While the object is detected and then measured, the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage, abnormal stopping, and disaster. Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement. To solve all these problems, this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to… More >

Tan Chen Tung¹, Uswah Khairuddin¹, Mohd Ibrahim Shapiai¹, Norhariani Md Nor^2,*, Mark Wen Han Hiew², Nurul Aisyah Mohd Suhaimie³

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1493-1508, 2023, DOI:10.32604/cmc.2023.029277 - 22 September 2022

Abstract Dairy farm management is crucial to maintain the longevity of the farm, and poor dairy youngstock or calf management could lead to gradually deteriorating calf health, which often causes premature death. This was found to be the most neglected part among the management workflows in Malaysia and has caused continuous loss over the recent years. Calf posture recognition is one of the effective methods to monitor calf behaviour and health state, which can be achieved by monitoring the calf behaviours of standing and lying where the former depicts active calf, and the latter, passive calf.… More >

Vani A. Hiremani^*, Kishore Kumar Senapati

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2603-2618, 2023, DOI:10.32604/csse.2023.027612 - 01 August 2022

Abstract The inter-class face classification problem is more reasonable than the intra-class classification problem. To address this issue, we have carried out empirical research on classifying Indian people to their geographical regions. This work aimed to construct a computational classification model for classifying Indian regional face images acquired from south and east regions of India, referring to human vision. We have created an Automated Human Intelligence System (AHIS) to evaluate human visual capabilities. Analysis of AHIS response showed that face shape is a discriminative feature among the other facial features. We have developed a modified convolutional… More >

He Gong^1,3,4, Mingwang Deng¹, Shijun Li^1,2,6,*, Tianli Hu^1,3,4, Yu Sun^1,3,4, Ye Mu^1,3,4, Zilian Wang¹, Chang Zhang¹, Thobela Louis Tyasi⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4953-4969, 2022, DOI:10.32604/cmc.2022.027457 - 28 July 2022

Abstract With the increasing intensive and large-scale development of the sika deer breeding industry, it is crucial to assess the health status of the sika deer by monitoring their behaviours. A machine vision–based method for the behaviour recognition of sika deer is proposed in this paper. Google Inception Net (GoogLeNet) is used to optimise the model in this paper. First, the number of layers and size of the model were reduced. Then, the 5 × 5 convolution was changed to two 3 × 3 convolutions, which reduced the parameters and increased the nonlinearity of the model.… More >

Erssa Arif^1,*, Syed Khuram Shahzad², Muhammad Waseem Iqbal³, Muhammad Arfan Jaffar⁴, Abdullah S. Alshahrani⁵, Ahmed Alghamdi⁶

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4615-4630, 2022, DOI:10.32604/cmc.2022.027571 - 21 April 2022

Abstract The conventional Close circuit television (CCTV) cameras-based surveillance and control systems require human resource supervision. Almost all the criminal activities take place using weapons mostly a handheld gun, revolver, pistol, swords etc. Therefore, automatic weapons detection is a vital requirement now a day. The current research is concerned about the real-time detection of weapons for the surveillance cameras with an implementation of weapon detection using Efficient–Net. Real time datasets, from local surveillance department's test sessions are used for model training and testing. Datasets consist of local environment images and videos from different type and resolution More >

Mirza Adnan Baig^*, Ghulam Ali Mallah, Noor Ahmed Shaikh

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4201-4213, 2022, DOI:10.32604/cmc.2022.026225 - 29 March 2022

Abstract Precipitation prediction (PP) have become one of the significant research areas of deep learning (DL) and machine vision (MV) techniques are frequently used to predict the weather variables (WV). Since the climate change has left significant impact upon weather variables (WV) and continuously changes are observed in temperature, humidity, cloud patterns and other factors. Although cloud images contain sufficient information to predict the precipitation pattern but due to changes in climate, the complex cloud patterns and rapid shape changing behavior of clouds are difficult to consider for rainfall prediction. Prediction of rainfall would provide more… More >