Synopsis
Cognitive computing is transforming how machines perceive, analyze, and make intelligent decisions, enabling breakthroughs in object detection, segmentation, and image processing. By integrating cognitive algorithms with machine learning, this technology enhances automation, accuracy, and efficiency across industries such as healthcare, finance, and agriculture. The ability of machines to mimic human reasoning opens new frontiers for innovation, leading to smarter diagnostics, risk assessments, and precision-driven solutions. As cognitive computing evolves, its applications will continue to reshape industries, improve decision-making, and drive technological advancements that impact society on a global scale. Navigating Challenges of Object Detection Through Cognitive Computing explores the challenges of object detection across various domains and presents cognitive computing-based intelligent techniques to overcome them. It provides insights into innovative methodologies for improving detection accuracy in complex scenarios such as surface defect detection, indoor environments, adverse weather conditions, UAV imagery, and camouflaged object detection. Covering topics such as smart engineering, social medial sentiment analyses, and healthcare, this book is an excellent resource for computer engineers, computer scientists, industry practitioners, professionals, researchers, scholars, academicians, and more.
About the Author
Sadique Ahmad (Member, IEEE) received the Ph.D. degree from the Department of Computer Sciences and Technology, Beijing Institute of Technology, China, in 2019, and the master's degree from the Department of Computer Sciences, IMSciences University, Peshawar, Pakistan, in 2015. Currently, he is associated with Prince Sultan University, Riyadh, Saudi Arabia as a Researcher. He has many collaborative scientific activities with international teams in different research projects in the following international universities. He has authored more than 67 research articles, which are published in peer-reviewed journals, books and conferences, including top journals, such as Information Sciences, Science China Information Sciences, Computational Intelligence and Neuroscience, Physica-A, and IEEE Access. Currently, he is focusing on Deep Cognitive Modeling for Trust Management in Social Cybersecurity, IoT, and Blockchain technologies. Previously, he worked on Cognitive Computing, Deep Cognitive Modeling for Students' Performance Prediction, and Cognitive Modeling in Object Detection using remote sensing images.
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