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- Volume 17, Issue 5, 2024
Recent Advances in Computer Science and Communications - Volume 17, Issue 5, 2024
Volume 17, Issue 5, 2024
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Cognitive Inherent SLR Enabled Survey for Software Defect Prediction
Authors: Anurag Mishra and Ashish SharmaIntroduction: Any software is created to help automate manual processes most of the time. It is expected from the developed software that it should perform the tasks it is supposed to do. Methods: More formally, it should work in a deterministic manner. Further, it should be capable of knowing if any provided input is not in the required format. Correctness of the software is inherent virtue that it should possess. Any rem Read More
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Multilevel Thresholding-based Medical Image Segmentation using Hybrid Particle Cuckoo Swarm Optimization
Authors: Dharmendra Kumar, Anil K. Solanki and Anil Kumar AhlawatBackground: The most important aspect of medical image processing and analysis is image segmentation. Fundamentally, the outcomes of segmentation have an impact on all subsequent image testing methods, including object representation and characterization, measuring of features, and even higher-level procedures. The problem with image segmentation is recognition and perceptual completion while segm Read More
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Maximizing Emotion Recognition Accuracy with Ensemble Techniques on EEG Signals
Authors: Sonu Kumar Jha, Somaraju Suvvari and Mukesh KumarBackground: Emotion is a strong feeling such as love, anger, fear, etc. Emotion can be recognized in two ways, i.e., External expression and Biomedical data-based. Nowadays, various research is occurring on emotion classification with biomedical data. Aim: One of the most current studies in the medical sector, gaming-based applications, education sector, and many other domains is EEG-based emotion identificatio Read More
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Enhancing Image Captioning Using Deep Convolutional Generative Adversarial Networks
Authors: Tarun Jaiswal, Manju Pandey and Priyanka TripathiIntroduction: Image caption generation has long been a fundamental challenge in the area of computer vision (CV) and natural language processing (NLP). In this research, we present an innovative approach that harnesses the power of Deep Convolutional Generative Adversarial Networks (DCGAN) and adversarial training to revolutionize the generation of natural and contextually relevant image captions. Method: Read More
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Face Recognition Using LBPH and CNN
Authors: Ratnesh Kumar Shukla, Arvind Kumar Tiwari and Ashish Ranjan MishraObjective: The purpose of this paper was to use Machine Learning (ML) techniques to extract facial features from images. Accurate face detection and recognition has long been a problem in computer vision. According to a recent study, Local Binary Pattern (LBP) is a superior facial descriptor for face recognition. A person's face may make their identity, feelings, and ideas more obvious. In the modern world, everyone wants to Read More
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Multimodal Medical Image Fusion based on the VGG19 Model in the NSCT Domain
Authors: ChunXiang Liu, Yuwei Wang, Tianqi Cheng, Xinping Guo and Lei WangAim: To deal with the drawbacks of the traditional medical image fusion methods, such as the low preservation ability of the details, the loss of edge information, and the image distortion, as well as the huge need for the training data for deep learning, a new multi-modal medical image fusion method based on the VGG19 model and the non-subsampled contourlet transform (NSCT) is proposed, whose overall objective is to sim Read More
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Segmentation Method of Concrete Small Cracks Based on UAV Images
More LessIntroduction: Cracks are one of the major problems in modern concrete buildings, especially in locations that are difficult to map manually, such as bridges and high-rise buildings. Accurate analysis of unmanned aerial vehicle (UAV) images has become the key to determining whether a building needs maintenance. Methods: Traditional image processing methods are easily interfered by high-frequency background. Neural networ Read More
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