The presence of cervical cancer is not apparent as its incubation period is long. A pap smear screening is the only diagnostic method;examining the pap smear slides uses a microscope. However, problems happen where hu...
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Feature selection (FS) is known as the most challenging problem in the Machine Learning field. FS can be considered an optimization problem that requires an efficient method to prepare its optimal subset of relative f...
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We present a quantum analysis of X-ray radiation generated from free electrons interacting with crystalline materials, revealing the role of the electron's quantum-wave nature and of the radiation's quantum-pa...
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Software development companies commonly use Global Software Development (GSD) in their industry. A competent Scrum team supports the success of the GSD project. This research aims to identify the game components in th...
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This paper introduces a personalized AI-based fitness tracker that provides dynamic diet and workout recommendations using the MERN stack, Llama 3 for natural language processing (NLP), and Hugging Face for machine le...
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Efficient parking management is a significant challenge in urban areas due to increasing vehicle density and limited space availability. This paper presents an automated parking management system that integrates real-...
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ISBN:
(数字)9798350357509
ISBN:
(纸本)9798350357516
Efficient parking management is a significant challenge in urban areas due to increasing vehicle density and limited space availability. This paper presents an automated parking management system that integrates real-time image processing and Optical Character Recognition (OCR) to detect vacant parking spaces and identify vehicle number plates, including both Bengali and English formats. The system utilizes deep learning models to address challenges such as low lighting, unstructured parking layouts, and diverse number plate formats. It is designed with a robust backend infrastructure, enabling real-time updates and parking space reservations. Tested in both simulated and real-world environments, the system achieves a parking space detection accuracy of 95.6% and a number plate recognition accuracy of 92.3%, with an average response time of 2.4 seconds for updating parking availability. This system provides a scalable and efficient solution for improving urban parking management.
Recent advances in language models (LMs), have demonstrated significant efficacy in tasks related to the arts and humanities. While LMs have exhibited exceptional performance across a wide range of natural language pr...
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The aim of this paper is to introduce the traffic congestion control system by using machine learning technology. Machine Learning is the property by which a computer system act without being explicitly programmed. It...
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Considering recent smart home solutions that automate home appliances through voice commands, elderly people and/or with special needs prefer using their mother-tongue. However, most of current systems adopt the Engli...
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Osteosarcoma is a type of malignant bone tumor that is reported across the *** advancements in Machine Learning(ML)and Deep Learning(DL)models enable the detection and classification of malignancies in biomedical *** ...
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Osteosarcoma is a type of malignant bone tumor that is reported across the *** advancements in Machine Learning(ML)and Deep Learning(DL)models enable the detection and classification of malignancies in biomedical *** this regard,the current study introduces a new Biomedical Osteosarcoma Image Classification using Elephant Herd Optimization and Deep Transfer Learning(BOIC-EHODTL)*** presented BOIC-EHODTL model examines the biomedical images to diagnose distinct kinds of *** the initial stage,Gabor Filter(GF)is applied as a pre-processing technique to get rid of the noise from *** addition,Adam optimizer with MixNet model is also employed as a feature extraction technique to generate feature ***,EHOalgorithm is utilized along with Adaptive Neuro-Fuzzy Classifier(ANFC)model for recognition and categorization of *** algorithm is utilized to fine-tune the parameters involved in ANFC model which in turn helps in accomplishing improved classification *** design of EHO with ANFC model for classification of osteosarcoma is the novelty of current *** order to demonstrate the improved performance of BOIC-EHODTL model,a comprehensive comparison was conducted between the proposed and existing models upon benchmark dataset and the results confirmed the better performance of BOIC-EHODTL model over recent methodologies.
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