Face recognition systems are essential in practically every industry in our digital age. One biometric that is frequently utilized is face recognition. It is helpful for security and has a ton of other advantages, ide...
详细信息
In autonomous driving systems, the monocular 3D object detection algorithm is a crucial component. The safety of autonomous vehicles heavily depends on a well-designed detection system. Therefore, developing a robust ...
详细信息
The severity of air pollution has prompted increased attention to air pollution monitoring. This article uses unmanned aerial vehicles (UAVs) to discover chimneys with excessive exhaust emissions (called 3E-chimneys) ...
详细信息
Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for perso...
详细信息
Handwriting is a unique and significant human feature that distinguishes them from one *** are many researchers have endeavored to develop writing recognition systems utilizing specific signatures or symbols for person identification through ***,such systems are susceptible to forgery,posing security *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** response to these challenges,we propose an innovative hybrid technique for individual identification based on independent handwriting,eliminating the reliance on specific signatures or *** innovative method is intricately designed,encompassing five distinct phases:data collection,preprocessing,feature extraction,significant feature selection,and *** key advancement lies in the creation of a novel dataset specifically tailored for Bengali handwriting(BHW),setting the foundation for our comprehensive ***-preprocessing,we embarked on an exhaustive feature extraction process,encompassing integration with kinematic,statistical,spatial,and composite *** meticulous amalgamation resulted in a robust set of 91 *** enhance the efficiency of our system,we employed an analysis of variance(ANOVA)F test and mutual information scores approach,meticulously selecting the most pertinent *** the identification phase,we harnessed the power of cutting-edge deep learning models,notably the Convolutional Neural Network(CNN)and Bidirectional Long Short-Term Memory(BiLSTM).These models underwent rigorous training and testing to accurately discern individuals based on their handwriting ***,our methodology introduces a groundbreaking hybrid model that synergizes CNN and BiLSTM,capitalizing on fine motor features for enhanced individual ***,our experimental results unde
Infectious lung diseases, such as pneumonia and COVID-19, pose significant threats to global health, with high mortality rates and substantial burdens on healthcare systems. Accurate and timely diagnosis is crucial fo...
详细信息
Infectious lung diseases, such as pneumonia and COVID-19, pose significant threats to global health, with high mortality rates and substantial burdens on healthcare systems. Accurate and timely diagnosis is crucial for effective management and treatment. This study addresses the limitations of existing diagnostic methods by proposing advanced techniques based on computer-aided diagnosis systems and enhanced machine-learning algorithms. The methodology involves the development of novel algorithms for image enhancement, segmentation, feature selection, and classification. A kurtosis-based multi-thresholding grasshopper optimization algorithm is proposed for image segmentation, reducing complexity and enhancing the accuracy of lesion identification. An improved rider optimization algorithm is also introduced for feature selection, aiming to prioritize relevant features and reduce dimensionality effectively. Furthermore, an enhanced support vector machine (SVM) algorithm for lesion classification is presented, utilizing linear mapping to generate feature scores for regions of interest. This facilitates the evaluation of the loss function and improves classification results. The approach’s effectiveness is demonstrated using datasets comprising chest X-ray and CT scan images from the LIDC-IDRI and Montgomery datasets. The improved optimization algorithms were trained and tested over the chest X-ray and CT scan image datasets. An improved SVM classified the lesions with an accuracy of 99.9% for chest X-ray images and 99.8% for CT scan images. The results proved that the improved SVM adequately classifies lung diseases from the chest X-ray and CT scan images. The findings suggest that the proposed methodologies significantly enhance the accuracy and efficiency of diagnosing pneumonia and COVID-19 from medical images. By addressing the limitations of existing diagnostic techniques, this research contributes to improving healthcare practices and ultimately reducing the burde
Poverty is still one of the factors that have been affecting the lives of humans over hundreds of decades in the world but still, it is not entirely eradicated. One of the main reasons is the lack of identification of...
详细信息
ISBN:
(纸本)9798350376913
Poverty is still one of the factors that have been affecting the lives of humans over hundreds of decades in the world but still, it is not entirely eradicated. One of the main reasons is the lack of identification of the economical pattern in a particular area that has been affected by poverty over a long period which has not been noted by any NGOs or government. So, that is the main reason why poverty eradication is still the first goal of UN sustainable development goals.[1] Understanding economical patterns over a region can lead us in providing informed policy-making, targeted NGO, and government-aided efforts. If we could track them down in an easy method at the earlier stage or in the advanced method and predict this fatal enigma on the region, the poverty can surely prevent or at least save lives. The above dilemma leads us to the essential method of tracking the reliable and timely measurements of economic activities, which are key for understanding economic development and designing government policies. But still many countries, especially developing countries, lack reliable data. Though data is available, the lack of quality in the data remains a huge challenge. In this paper, we propose a low-cost yet efficient approach to predict the economical pattern in a rural region from satellite imagery, which is globally available, in the meantime, satellite images are continuously updating to the changeable environmental conditions. Since the satellite image is way more advantageous than traditional methods, they play a huge role in the model. Traditional methods like surveys are expensive to conduct and include a lot of manpower. [2]This contributes to infer socioeconomic indicators from large-scale, remotely-sensed data. The available dataset is used to extract the luminous intensity from the night-time satellite images and added along with the other features of the particular region that determines the socio- economic conditions. Then with machine learning al
Today for an organisation, data security is the most crucial topic. An organisation needs to protect its information against cyberattacks. Cryptography, DLT, and blockchain technology provide higher security for data ...
详细信息
Smart Classrooms (SCR) are reshaping the learning experience with their interactive technology and personalized knowledge, leading to improved student engagement by seamlessly integrating digital gadgets. In this rapi...
详细信息
The user’s intent to seek online information has been an active area of research in user *** profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and *** u...
详细信息
The user’s intent to seek online information has been an active area of research in user *** profiling considers user characteristics,behaviors,activities,and preferences to sketch user intentions,interests,and *** user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content *** user’s complete online experience in seeking information is a blend of activities such as searching,verifying,and sharing it on social ***,a combination of multiple behaviors in profiling users has yet to be *** research takes a novel approach and explores user intent types based on multidimensional online behavior in information *** research explores information search,verification,and dissemination behavior and identifies diverse types of users based on their online engagement using machine *** research proposes a generic user profile template that explains the user characteristics based on the internet experience and uses it as ground truth for data *** feedback is based on online behavior and practices collected by using a survey *** participants include both males and females from different occupation sectors and different *** data collected is subject to feature engineering,and the significant features are presented to unsupervised machine learning methods to identify user intent classes or profiles and their *** techniques are evaluated,and the K-Mean clustering method successfully generates five user groups observing different user characteristics with an average silhouette of 0.36 and a distortion score of *** average is computed to identify user intent type *** user intent classes are then further generalized to create a user intent template with an Inter-Rater Reliability of 75%.This research successfully extracts different user types based on th
In 21st century, AI-based intelligent recommendation system uses rating predictions, which are frequently utilized and helps users swiftly filter down their options and make informed judgements from an abundance of ma...
详细信息
暂无评论