This project aims to employ DL and ML techniques to predict ragas in Indian classical music accurately. The focus is on developing a system that can process audio recordings and make precise raga predictions. The clas...
详细信息
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health withou...
详细信息
In today’s growing modern world environment,as human food activities are changing,it is affecting human health,thus leading to diseases like *** is a complex disease with many subtypes that affect human health without premature treatment and cause *** the analysis of early diagnosis and prognosis of cancer studies can improve clinical management by analyzing various features of observa-tion,which has become necessary to classify the type in cancer *** research needs importance to organize the risk of the cancer patients based on data analysis to predict the result of premature *** paper introduces a Maximal Region-Based Candidate Feature Selection(MRCFS)for early risk diagnosing using Soft-Max Feed Forward Neural Classification(SMF2NC)to solve the above *** predictive model is based on a different relational feature learning model,which is possessed to candidate selection to reduce the *** redundant features are processed marginal weight rates for observing similar features’variants and the absolute *** neural hidden layers are trained using the Sigmoid Activation Function(SAF)to create the logical condition for feed-forward ***,the maximal features are introduced to invite a deep neural network con-structed on the Feed Forward Recurrent Neural Network(FFRNN).The classifier produces higher classification accuracy than the previous methods and observes the cancer detection,which is recommended for early diagnosis.
Because of recent COVID-19 epidemic, the Internet-of-Medical-Things (IoMT) has acquired a significant impetus to diagnose patients remotely, regulate medical equipment, and track quarantined patients via smart electro...
详细信息
In the realm of agricultural automation, the precise identification of crop stress holds immense significance for enhancing crop productivity. Existing methods primarily focus on controlled environments, which may not...
详细信息
Load Forecast (LF) is an important task in the planning, control and application of public power systems. Accurate Short Term Load Forecast (STLF) is the premise of safe and economical operation of a power system. In ...
详细信息
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of ...
详细信息
Cloud storage is essential for managing user data to store and retrieve from the distributed data *** storage service is distributed as pay a service for accessing the size to collect the *** to the massive amount of data stored in the data centre containing similar information and file structures remaining in multi-copy,duplication leads to increase storage *** potential deduplication system doesn’t make efficient data reduction because of inaccuracy in finding similar data *** creates a complex nature to increase the storage consumption under *** resolve this problem,this paper proposes an efficient storage reduction called Hash-Indexing Block-based Deduplication(HIBD)based on Segmented Bind Linkage(SBL)Methods for reducing storage in a cloud ***,preprocessing is done using the sparse augmentation ***,the preprocessed files are segmented into blocks to make *** block of the contents is compared with other files through Semantic Content Source Deduplication(SCSD),which identifies the similar content presence between the *** on the content presence count,the Distance Vector Weightage Correlation(DVWC)estimates the document similarity weight,and related files are grouped into a ***,the segmented bind linkage compares the document to find duplicate content in the cluster using similarity weight based on the coefficient match *** implementation helps identify the data redundancy efficiently and reduces the service cost in distributed cloud storage.
Enhancement of technology yields more complex time-dependent outcomes for better understanding and analysis. These outcomes generate more complex, unstable, and high-dimensional data from non-stationary environments. ...
详细信息
Face recognition is a fast-growing technology that is widely used in forensics such as criminal identification, secure access, and prison *** contrasts from other classification issues in that there are normally a mor...
详细信息
The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care *** diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely ...
详细信息
The coronavirus disease 2019(COVID-19)has severely disrupted both human life and the health care *** diagnosis and treatment have become increasingly important;however,the distribution and size of lesions vary widely among individuals,making it challenging to accurately diagnose the *** study proposed a deep-learning disease diagnosismodel based onweakly supervised learning and clustering visualization(W_CVNet)that fused classification with ***,the data were *** optimizable weakly supervised segmentation preprocessing method(O-WSSPM)was used to remove redundant data and solve the category imbalance ***,a deep-learning fusion method was used for feature extraction and classification recognition.A dual asymmetric complementary bilinear feature extraction method(D-CBM)was used to fully extract complementary features,which solved the problem of insufficient feature extraction by a single deep learning ***,an unsupervised learning method based on Fuzzy C-Means(FCM)clustering was used to segment and visualize COVID-19 lesions enabling physicians to accurately assess lesion distribution and disease *** this study,5-fold cross-validation methods were used,and the results showed that the network had an average classification accuracy of 85.8%,outperforming six recent advanced classification models.W_CVNet can effectively help physicians with automated aid in diagnosis to determine if the disease is present and,in the case of COVID-19 patients,to further predict the area of the lesion.
Computing strongly connected components (SCC) is a key operation for many applications on directed graphs. Specifically, a SCC of a directed graph G is one of its maximal subgraphs, in which any two nodes are reachabl...
详细信息
暂无评论