Digital information literacy competencies among pg students of CCS Haryana Agricultural University, Hisar: A study

Parmar, Seema; Pateria, Rajive Kumar

doi:10.5958/2249-5576.2020.00015.1

Cited by 1 publication

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…is electronic information usually involves a wide range of types, and most of them do not match the user's search target, resulting in low search efficiency [8]. Parmar and Pateria expressed that there is an urgent need for an efficient and accurate automatic electronic information classification system to complete the classification of electronic information [9]. Some people such as Grigoryev et al believe that electronic information classification has excellent performance not only in search engines, but also in information push services and information filtering.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

2022

Security and Communication Networks

View full text Add to dashboard Cite

In order to make up for the shortcomings of traditional electronic information characteristics and classification recognition algorithms and improve the application ability of the technology, a special extraction algorithm based on the performance of deep multilayer autoencoders is required, and the training of deep learning network model is not supervised with pretraining and the supervision of the margin-based Fisher guidelines. The regularization means in the process of data generating pretraining and carving will prevent the prefining training. Experimental results on multiple data distributions further determine the efficiency of the algorithm. By analyzing the depth learning model, the image information in electronic information is used as an example, and its extraction technology is discussed, and the direction is indicated further. The experimental results show that the acceptance performance of the DMFA algorithm is improved in some cases compared with similar algorithms. And in Ionosphere, PIMA, IRIS Data Set this algorithm acquires the improvement effect, but the results obtained in other data sets are not ideal, thereby obtaining the most use of electronic information feature extraction and classification recognition.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

2022

Security and Communication Networks

View full text Add to dashboard Cite

show abstract

Digital information literacy competencies among pg students of CCS Haryana Agricultural University, Hisar: A study

Cited by 1 publication

References 0 publications

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

Research on Electronic Information Feature Extraction and Classification Recognition Algorithm Based on Deep Learning

Contact Info

Product

Resources

About