Farah Deeba

599 total citations
26 papers, 429 citations indexed

About

Farah Deeba is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Information Systems. According to data from OpenAlex, Farah Deeba has authored 26 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 12 papers in Media Technology and 3 papers in Information Systems. Recurrent topics in Farah Deeba's work include Advanced Image Processing Techniques (12 papers), Advanced Image Fusion Techniques (9 papers) and Image and Signal Denoising Methods (7 papers). Farah Deeba is often cited by papers focused on Advanced Image Processing Techniques (12 papers), Advanced Image Fusion Techniques (9 papers) and Image and Signal Denoising Methods (7 papers). Farah Deeba collaborates with scholars based in China, Pakistan and South Korea. Farah Deeba's co-authors include Fayaz Ali Dharejo, Yuanchun Zhou, Kun She, Yi Du, Aftab Ahmed, Munsif Ali Jatoi, Muhammad Zawish, Ashutosh Bagchi, Xuezhi Wang and Bhagwan Das and has published in prestigious journals such as IEEE Access, Electronics Letters and IEEE Geoscience and Remote Sensing Letters.

In The Last Decade

Farah Deeba

26 papers receiving 406 citations

Peers

Countries citing papers authored by Farah Deeba

Since Specialization

Citations

This map shows the geographic impact of Farah Deeba's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Farah Deeba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Farah Deeba more than expected).

Fields of papers citing papers by Farah Deeba

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Farah Deeba. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Farah Deeba. The network helps show where Farah Deeba may publish in the future.

Co-authorship network of co-authors of Farah Deeba

This figure shows the co-authorship network connecting the top 25 collaborators of Farah Deeba. A scholar is included among the top collaborators of Farah Deeba based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Farah Deeba. Farah Deeba is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Title	Journal	Authors	Indexed citations
1	Multimodal-Boost: Multimodal Medical Image Super-Resolution Using Multi-Attention Network With Wavelet Transform	IEEE/ACM Transactions on Computational Biology and Bioinformatics	Fayaz Ali Dharejo, Muhammad Zawish et al.	25
2	Digital image watermarking in sparse domain	Information Security Journal A Global Perspective	Farah Deeba, Fayaz Ali Dharejo et al.	2
3	Multi-scale Single Image Super-Resolution with Remote-Sensing Application Using Transferred Wide Residual Network	Wireless Personal Communications	Farah Deeba, Yuanchun Zhou et al.	8
4	TWIST-GAN: Towards Wavelet Transform and Transferred GAN for Spatio-Temporal Single Image Super Resolution	ACM Transactions on Intelligent Systems and Technology	Fayaz Ali Dharejo, Farah Deeba et al.	32
5	A novel image dehazing framework for robust vision‐based intelligent systems	International Journal of Intelligent Systems	Farah Deeba, Fayaz Ali Dharejo et al.	13
6	A deep hybrid neural network for single image dehazing via wavelet transform	Optik	Fayaz Ali Dharejo, Yuanchun Zhou et al.	23
7	A plexus‐convolutional neural network framework for fast remote sensing image super‐resolution in wavelet domain	IET Image Processing	Farah Deeba, Yuanchun Zhou et al.	10
8	Toward developing tangling noise removal and blind inpainting mechanism based on total variation in image processing	Electronics Letters	Muhammad Ashfaq Khan, Fayaz Ali Dharejo et al.	11
9	Digital Watermarking Using Deep Neural Network	International Journal of Machine Learning and Computing	Farah Deeba, Kun She et al.	27
10	Single Image Super-Resolution with Application to Remote-Sensing Image		Farah Deeba, Fayaz Ali Dharejo et al.	4
11	A remote‐sensing image enhancement algorithm based on patch‐wise dark channel prior and histogram equalisation with colour correction	IET Image Processing	Fayaz Ali Dharejo, Yuanchun Zhou et al.	23
12	Sparse representation based computed tomography images reconstruction by coupled dictionary learning algorithm	IET Image Processing	Farah Deeba, Kun She et al.	24
13	Digital image watermarking based on ANN and least significant bit	Information Security Journal A Global Perspective	Farah Deeba, Kun She et al.	9
14	Lossless digital image watermarking in sparse domain by using K‐singular value decomposition algorithm	IET Image Processing	Farah Deeba, Kun She et al.	17
15	A simple and cost-effective optical fiber angle measurement sensor using polymer optical fiber based on the TMBC	Optical Fiber Technology	Abdul Ghaffar, Wenyi Liu et al.	21
16	Protecting the Intellectual Properties of Digital Watermark Using Deep Neural Network		Farah Deeba et al.	2
17	A Color Enhancement Scene Estimation Approach for Single Image Haze Removal	IEEE Geoscience and Remote Sensing Letters	Fayaz Ali Dharejo, Yuanchun Zhou et al.	26
18	Data transformation of UML diagram by using model driven architecture		Farah Deeba, Kun She et al.	10
19	Analyzing Virtual Machine Live Migration in Application Data Context	International Journal of Advanced Computer Science and Applications	Asadullah Shaikh, Muhammad Ali et al.	2
20	Health Monitoring of Structures Using Statistical Pattern Recognition Techniques	Journal of Performance of Constructed Facilities	Farah Deeba, Ashutosh Bagchi et al.	27

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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