This book gathers outstanding research papers presented at the International Joint Conference on Advances in Computational Intelligence (IJCACI 2020), organized by Daffodil International University (DIU) and Jahangirnagar University (JU) in Bangladesh and South Asian University (SAU) in India. These proceedings present novel contributions in the areas of computational intelligence and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for automatic visual understanding and recognition which finds huge applications in agricultural productions. It also entails how rendering of machine learning techniques to computer vision algorithms is boosting this sector with better productivity by developing more precise systems. Computer vision and machine learning (CV-ML) helps in plant disease assessment along with crop condition monitoring to control the degradation of yield, quality, and severe financial loss for farmers. Significant scientific and technological advances have been made in defect assessment, quality grading, disease recognition, pests, insects, fruits, and vegetable types recognition and evaluation of a wide range of agricultural plants, crops, leaves, and fruits. The book discusses intelligent robots developed with the touch of CV-ML which can help farmers to perform various tasks like planting, weeding, harvesting, plant health monitoring, and so on. The topics covered in the book include plant, leaf, and fruit disease detection, crop health monitoring, applications of robots in agriculture, precision farming, assessment of product quality and defects, pest, insect, fruits, and vegetable types recognition.

This book is a collection of best selected high-quality research papers presented at the International Conference on Advances in Energy Management (ICAEM 2019) organized by the Department of Electrical Engineering, Jodhpur Institute of Engineering & Technology (JIET), Jodhpur, India, during 20-21 December 2019. The book discusses intelligent energy management technologies which are cost effective compared to the high cost of fossil fuels. This book also explains why these systems have beneficial impact on environmental, economic and political issues of the world. The book is immensely useful for research scholars, academicians, R&D institutions, practicing engineers and managers from industry.

This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2019), held at the University of Liberal Arts Bangladesh (ULAB), Dhaka, on 25-26 October 2019 and jointly organized by the University of Liberal Arts Bangladesh (ULAB), Bangladesh; Jahangirnagar University (JU), Bangladesh; and South Asian University (SAU), India. These proceedings present novel contributions in the areas of computational intelligence, and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book gathers outstanding research papers presented at the International Joint Conference on Advances in Computational Intelligence (IJCACI 2020), organized by Daffodil International University (DIU) and Jahangirnagar University (JU) in Bangladesh and South Asian University (SAU) in India. These proceedings present novel contributions in the areas of computational intelligence and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for automatic visual understanding and recognition which finds huge applications in agricultural productions. It also entails how rendering of machine learning techniques to computer vision algorithms is boosting this sector with better productivity by developing more precise systems. Computer vision and machine learning (CV-ML) helps in plant disease assessment along with crop condition monitoring to control the degradation of yield, quality, and severe financial loss for farmers. Significant scientific and technological advances have been made in defect assessment, quality grading, disease recognition, pests, insects, fruits, and vegetable types recognition and evaluation of a wide range of agricultural plants, crops, leaves, and fruits. The book discusses intelligent robots developed with the touch of CV-ML which can help farmers to perform various tasks like planting, weeding, harvesting, plant health monitoring, and so on. The topics covered in the book include plant, leaf, and fruit disease detection, crop health monitoring, applications of robots in agriculture, precision farming, assessment of product quality and defects, pest, insect, fruits, and vegetable types recognition.

This book is a collection of best selected high-quality research papers presented at the International Conference on Advances in Energy Management (ICAEM 2019) organized by the Department of Electrical Engineering, Jodhpur Institute of Engineering & Technology (JIET), Jodhpur, India, during 20-21 December 2019. The book discusses intelligent energy management technologies which are cost effective compared to the high cost of fossil fuels. This book also explains why these systems have beneficial impact on environmental, economic and political issues of the world. The book is immensely useful for research scholars, academicians, R&D institutions, practicing engineers and managers from industry.

This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14-15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2019), held at the University of Liberal Arts Bangladesh (ULAB), Dhaka, on 25-26 October 2019 and jointly organized by the University of Liberal Arts Bangladesh (ULAB), Bangladesh; Jahangirnagar University (JU), Bangladesh; and South Asian University (SAU), India. These proceedings present novel contributions in the areas of computational intelligence, and offer valuable reference material for advanced research. The topics covered include collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book gathers outstanding research papers presented at the International Joint Conference on Computational Intelligence (IJCCI 2018), which was held at Daffodil International University on 14-15 December 2018. The topics covered include: collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book is as an extension of previous book "Computer Vision and Machine Learning in Agriculture" for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.

This book gathers outstanding research papers presented at the 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021), held online during October 23–24, 2021.  IJCACI 2021 is jointly organized by Jahangirnagar University (JU), Bangladesh, and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

This book is as an extension of previous book “Computer Vision and Machine Learning in Agriculture� for academicians, researchers, and professionals interested in solving the problems of agricultural plants and products for boosting production by rendering the advanced machine learning including deep learning tools and techniques to computer vision algorithms. The book contains 15 chapters. The first three chapters are devoted to crops harvesting, weed, and multi-class crops detection with the help of robots and UAVs through machine learning and deep learning algorithms for smart agriculture. Next, two chapters describe agricultural data retrievals and data collections. Chapters 6, 7, 8 and 9 focuses on yield estimation, crop maturity detection, agri-food product quality assessment, and medicinal plant recognition, respectively. The remaining six chapters concentrates on optimized disease recognition through computer vision-based machine and deep learning strategies.

This book gathers outstanding research papers presented at the 5th International Joint Conference on Advances in Computational Intelligence (IJCACI 2021), held online during October 23-24, 2021. IJCACI 2021 is jointly organized by Jahangirnagar University (JU), Bangladesh, and South Asian University (SAU), India. The book presents the novel contributions in areas of computational intelligence and it serves as a reference material for advance research. The topics covered are collective intelligence, soft computing, optimization, cloud computing, machine learning, intelligent software, robotics, data science, data security, big data analytics, and signal and natural language processing.

Large image databases find diverse applications in real-life situations. It is essential to develop an efficient technique to grasp required information from these databases. Fast retrieval and robustness are two main criteria for efficient recognition of an object using image databases. Keeping this in mind, the present research work describes a hybrid method using a weighted combination of multiple image features mainly color histogram, distance, and moment parameters for trademark recognition. The computational power is accelerated by employing a low cost NVIDIA's Compute Unified Device Architecture (CUDA) enabled GPU. Our experimental results show that this new technique provides more robust performance than either of the individual methods and our GPU implementation requires less than 50% of the CPU computation time. This experimentation demonstrates that the method based on multiple weighted images features with cooperative implementation between the CPU and GPU is an effective way of image retrieval from large databases.