Ammar Amjad

471 total citations
11 papers, 292 citations indexed

About

Ammar Amjad is a scholar working on Signal Processing, Artificial Intelligence and Experimental and Cognitive Psychology. According to data from OpenAlex, Ammar Amjad has authored 11 papers receiving a total of 292 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Signal Processing, 4 papers in Artificial Intelligence and 4 papers in Experimental and Cognitive Psychology. Recurrent topics in Ammar Amjad's work include Emotion and Mood Recognition (4 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (4 papers). Ammar Amjad is often cited by papers focused on Emotion and Mood Recognition (4 papers), Speech and Audio Processing (4 papers) and Music and Audio Processing (4 papers). Ammar Amjad collaborates with scholars based in Taiwan, Mexico and Pakistan. Ammar Amjad's co-authors include Hsien-Tsung Chang, Lal Khan, Noman Ashraf, Alexander Gelbukh, Sufian Hameed, Jawwad Ahmed Shamsi, Cheng-Hsuan Wu and Li‐Chia Tai and has published in prestigious journals such as Scientific Reports, IEEE Access and Applied Sciences.

In The Last Decade

Ammar Amjad

10 papers receiving 285 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ammar Amjad Taiwan	8	229	43	39	36	18	11	292
Lal Khan Taiwan	8	253 1.1×	38 0.9×	37 0.9×	40 1.1×	25 1.4×	15	334
Noman Ashraf Mexico	10	244 1.1×	29 0.7×	47 1.2×	21 0.6×	24 1.3×	14	290
Burcu Can Türkiye	9	192 0.8×	25 0.6×	44 1.1×	10 0.3×	6 0.3×	38	251
Meng Zhao China	8	318 1.4×	23 0.5×	45 1.2×	11 0.3×	18 1.0×	34	380
C. N. Subalalitha India	10	358 1.6×	30 0.7×	64 1.6×	20 0.6×	37 2.1×	23	393
Ashraf Kamal India	6	185 0.8×	24 0.6×	49 1.3×	18 0.5×	18 1.0×	8	218
Kaisong Song China	11	282 1.2×	13 0.3×	71 1.8×	16 0.4×	18 1.0×	28	315
Michael Baeriswyl Switzerland	7	193 0.8×	29 0.7×	39 1.0×	20 0.6×	5 0.3×	11	251
Ján Staš Slovakia	7	132 0.6×	36 0.8×	30 0.8×	12 0.3×	6 0.3×	45	190
Jingye Li China	10	403 1.8×	13 0.3×	34 0.9×	43 1.2×	12 0.7×	14	427

Countries citing papers authored by Ammar Amjad

Since Specialization

Citations

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

Fields of papers citing papers by Ammar Amjad

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ammar Amjad

This figure shows the co-authorship network connecting the top 25 collaborators of Ammar Amjad. A scholar is included among the top collaborators of Ammar Amjad 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 Ammar Amjad. Ammar Amjad 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:

11 of 11 papers shown

1.

Amjad, Ammar, et al.. (2025). Dynamic fire and smoke detection module with enhanced feature integration and attention mechanisms. Pattern Analysis and Applications. 28(2).

2.

Amjad, Ammar, et al.. (2024). Multi-Domain Emotion Recognition Enhancement: A Novel Domain Adaptation Technique for Speech-Emotion Recognition. IEEE Transactions on Audio Speech and Language Processing. 33. 528–541. 1 indexed citations

3.

Amjad, Ammar, Lal Khan, & Hsien-Tsung Chang. (2022). Data augmentation and deep neural networks for the classification of Pakistani racial speakers recognition. PeerJ Computer Science. 8. e1053–e1053. 7 indexed citations

4.

Amjad, Ammar, et al.. (2022). Recognizing Semi-Natural and Spontaneous Speech Emotions Using Deep Neural Networks. IEEE Access. 10. 37149–37163. 14 indexed citations

5.

Khan, Lal, Ammar Amjad, Noman Ashraf, & Hsien-Tsung Chang. (2022). Multi-class sentiment analysis of urdu text using multilingual BERT. Scientific Reports. 12(1). 5436–5436. 66 indexed citations

6.

Khan, Lal, et al.. (2022). Deep Sentiment Analysis Using CNN-LSTM Architecture of English and Roman Urdu Text Shared in Social Media. Applied Sciences. 12(5). 2694–2694. 91 indexed citations

7.

Amjad, Ammar, Lal Khan, & Hsien-Tsung Chang. (2021). Semi-Natural and Spontaneous Speech Recognition Using Deep Neural Networks with Hybrid Features Unification. Processes. 9(12). 2286–2286. 14 indexed citations

8.

Khan, Lal, Ammar Amjad, Noman Ashraf, Hsien-Tsung Chang, & Alexander Gelbukh. (2021). Urdu Sentiment Analysis With Deep Learning Methods. IEEE Access. 9. 97803–97812. 67 indexed citations

9.

Amjad, Ammar, Lal Khan, & Hsien-Tsung Chang. (2021). Effect on speech emotion classification of a feature selection approach using a convolutional neural network. PeerJ Computer Science. 7. e766–e766. 24 indexed citations

10.

Wu, Cheng-Hsuan, Hsien-Tsung Chang, & Ammar Amjad. (2020). Eye in-painting using WGAN-GP for face images with mosaic. 68–68. 1 indexed citations

11.

Shamsi, Jawwad Ahmed, et al.. (2014). Clicksafe: Providing Security against Clickjacking Attacks. 206–210. 7 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.

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