Rachid Sammouda

481 total citations
34 papers, 335 citations indexed

About

Rachid Sammouda is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Neurology. According to data from OpenAlex, Rachid Sammouda has authored 34 papers receiving a total of 335 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 16 papers in Artificial Intelligence and 8 papers in Neurology. Recurrent topics in Rachid Sammouda's work include Neural Networks and Applications (13 papers), Medical Image Segmentation Techniques (9 papers) and Image and Signal Denoising Methods (8 papers). Rachid Sammouda is often cited by papers focused on Neural Networks and Applications (13 papers), Medical Image Segmentation Techniques (9 papers) and Image and Signal Denoising Methods (8 papers). Rachid Sammouda collaborates with scholars based in Saudi Arabia, Japan and United Arab Emirates. Rachid Sammouda's co-authors include Ali El‐Zaart, Noboru Niki, Fatma Taher, Naoufel Werghi, Hussain Al-Ahmad, H. Nishitani, Nuru Adgaba, Ahmed Alghamdi, Hiromu Nishitani and Duaa AlSaeed and has published in prestigious journals such as Computers in Human Behavior, Pattern Recognition and IEEE Transactions on Nuclear Science.

In The Last Decade

Rachid Sammouda

34 papers receiving 304 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Rachid Sammouda Saudi Arabia	9	135	119	71	54	44	34	335
Mighty Abra Ayidzoe Ghana	7	131 1.0×	141 1.2×	25 0.4×	69 1.3×	43 1.0×	17	422
Patrick Kwabena Mensah Ghana	7	117 0.9×	119 1.0×	23 0.3×	64 1.2×	42 1.0×	27	371
Edmar Rezende Brazil	7	209 1.5×	130 1.1×	46 0.6×	138 2.6×	28 0.6×	8	497
Youlian Zhu China	7	174 1.3×	60 0.5×	60 0.8×	50 0.9×	33 0.8×	18	320
Xiwang Xie China	10	253 1.9×	111 0.9×	87 1.2×	62 1.1×	43 1.0×	18	466
Mushtaq Ali Pakistan	11	202 1.5×	87 0.7×	43 0.6×	40 0.7×	54 1.2×	33	386
Yuncong Feng China	12	242 1.8×	86 0.7×	159 2.2×	48 0.9×	44 1.0×	30	444
Shaveta Arora India	9	290 2.1×	105 0.9×	120 1.7×	113 2.1×	50 1.1×	33	459
Musa Çıbuk Türkiye	8	104 0.8×	141 1.2×	17 0.2×	127 2.4×	34 0.8×	20	358

Countries citing papers authored by Rachid Sammouda

Since Specialization

Citations

This map shows the geographic impact of Rachid Sammouda'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 Rachid Sammouda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachid Sammouda more than expected).

Fields of papers citing papers by Rachid Sammouda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rachid Sammouda. 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 Rachid Sammouda. The network helps show where Rachid Sammouda may publish in the future.

Co-authorship network of co-authors of Rachid Sammouda

This figure shows the co-authorship network connecting the top 25 collaborators of Rachid Sammouda. A scholar is included among the top collaborators of Rachid Sammouda 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 Rachid Sammouda. Rachid Sammouda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Sammouda, Rachid & Ali El‐Zaart. (2021). An Optimized Approach for Prostate Image Segmentation Using K‐Means Clustering Algorithm with Elbow Method. Computational Intelligence and Neuroscience. 2021(1). 4553832–4553832. 55 indexed citations

Sammouda, Rachid. (2016). Prostate Cancer Diagnosis Based on the Segmentation and Analysis of NIR Images Obtained Using Two PSMA-1 Based PDT Conjugates PSMA-1-Pc413 and PSMA-1-IR700. International Journal of Sciences: Basic and Applied Research. 25(2). 218–232. 1 indexed citations

Sammouda, Rachid, Xinning Wang, & James P. Basilion. (2015). Hopfield Neural Network for the segmentation of Near Infrared Fluorescent images for diagnosing prostate cancer. 111–118. 3 indexed citations

Sammouda, Rachid. (2015). Lung Region Segmentation using Artificial Neural Network Hopfield Model for Cancer Diagnosis in Thorax CT Images. 3(2). 19–19. 1 indexed citations

Sammouda, Rachid, et al.. (2013). Adapting artificial hopfield neural network for agriculture satellite image segmentation. 1–7. 2 indexed citations

AlSaeed, Duaa, Ahmed Bouridane, Ali El‐Zaart, & Rachid Sammouda. (2012). Two modified Otsu image segmentation methods based on Lognormal and Gamma distribution models. 1–5. 28 indexed citations

Sammouda, Rachid, et al.. (2012). A content based image retrieval using K-means algorithm. 1908. 221–225. 6 indexed citations

AlSaeed, Duaa, Ahmed Bouridane, Ali El‐Zaart, & Rachid Sammouda. (2012). Novel fingerprint segmentation with entropy-Li MCET using log-normal distribution. B6–B6. 1 indexed citations

Werghi, Naoufel, et al.. (2010). An unsupervised learning approach based on a Hopfield-like network for assessing posterior capsule opacification. Pattern Analysis and Applications. 13(4). 383–396. 1 indexed citations

10.

Sammouda, Rachid. (2010). Data-Dependent Weight Initialization in the Hopfield Neural Network Classifier: Application to Natural Colour Images. International Journal of Computers and Applications. 32(2). 242–249. 1 indexed citations

11.

Sammouda, Rachid, et al.. (2004). Modification of the mean-square error principle to double the convergence speed of a special case of Hopfield neural network used to segment pathological liver color images. BMC Medical Informatics and Decision Making. 4(1). 22–22. 2 indexed citations

12.

Sammouda, Rachid, et al.. (2003). Segmentation and analysis of liver cancer pathological color images based on artificial neural networks. 3. 392–396. 5 indexed citations

13.

Sammouda, Rachid, et al.. (2002). Cancerous nuclei detection on digitized pathological lung color images. Computers and Biomedical Research. 35(2). 92–98. 2 indexed citations

14.

Sammouda, Rachid, et al.. (2002). Cancerous nuclei detection on digitized pathological lung color images. Journal of Biomedical Informatics. 35(2). 92–98. 5 indexed citations

15.

Sammouda, Rachid, et al.. (2002). Liver Cancer Detection System Based on the Analysis of Digitized Color Images of Tissue Samples Obtained Using Needle Biopsy. Information Visualization. 1(2). 130–138. 7 indexed citations

16.

Sammouda, Rachid, et al.. (1999). Segmentation and Analysis of Liver Cancer Pathological Color Images based on Artificial Neural Networks. 17(4). 453–454. 1 indexed citations

17.

Sammouda, Rachid, et al.. (1998). Segmentation of Sputum Color Image for Lung Cancer Diagnosis Based on Neural Networks. IEICE Transactions on Information and Systems. 81(8). 862–871. 13 indexed citations

18.

Sammouda, Rachid, Noboru Niki, Hiroshi Nishitani, Shuichi Nakamura, & Shinichiro Mori. (1997). <title>Unsupervised sputum color image segmentation for lung cancer diagnosis based on a Hopfield neural network</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 3034. 889–899. 1 indexed citations

19.

Sammouda, Rachid, Noboru Niki, & Hiromu Nishitani. (1996). Segmentation of Brain MR Images Based on Neural Networks. IEICE Transactions on Information and Systems. 79(4). 349–356. 8 indexed citations

20.

Sammouda, Rachid, Noboru Niki, & Hiromu Nishitani. (1995). Neural networks for the segmentation of magnetic resonance images. Lecture notes in computer science. 1024. 339–346. 1 indexed citations

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.

Explore authors with similar magnitude of impact