Researchers from the University of Tartu Institute of Physics have developed a novel method for enhancing the quality of three-dimensional images by increasing the depth of focus in holograms fivefold ...
Abstract: Dementia, a neurodegenerative disorder, requires early prediction and effective diagnosis for providing better treatment to avert the loss. The detection and classification of disease is ...
Abstract: Landslides pose a significant threat to life and property. This research aims to develop a machine-learning model to predict landslide occurrences, focusing on logistic regression. Key ...
Abstract: The Multiple Signal Classification (MUSIC) algorithm, a widely used Direction of Arrival (DOA) estimation algorithm, has the disadvantage of being unable to estimate coherent signals, and ...
Abstract: The traditional fixed-step-size LMS (Least Mean Squares) algorithm has the problems of slow convergence speed and limited real-time performance in music signal denoising. This paper proposes ...
Abstract: Sonar signal processing plays an important role in extracting information from the unprocessed acoustic data. The processed data ensures accurate target identification. This paper represents ...
Abstract: Artificial Intelligence (AI) is revolutionising the telecommunications industry by enhancing signal processing, network management, and overall system performance. With the rise of 5G and ...
Abstract: Plant disease identification through leaves is an important aspect of crop health management for achieving the highest productivity. This research work compares the use of pre-trained ...
Abstract: Avocado cultivation is a rapidly growing industry known for its creamy, nutritious fruit and economic value In Tamil Nadu the plane bear fruits for a period of 3 to 4 years after which tree ...
Industry-Leading Signal Processing and Algorithms Deliver Precise and Low Touch-Display Interference Across a Wide Range of OLED Panel Architecture ...
Abstract: In India, countless children are reported missing every year, with a significant percentage remaining untraced due to challenges in identification and limited resources. This project ...
Abstract: This paper proposes a data analysis model integrating linear regression, principal component analysis and non-negative matrix decomposition, focusing on data transformation, dimensionality ...
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