Narit Hnoohom

1.1k total citations
84 papers, 725 citations indexed

About

Narit Hnoohom is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Artificial Intelligence. According to data from OpenAlex, Narit Hnoohom has authored 84 papers receiving a total of 725 indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Computer Vision and Pattern Recognition, 19 papers in Biomedical Engineering and 17 papers in Artificial Intelligence. Recurrent topics in Narit Hnoohom's work include Context-Aware Activity Recognition Systems (30 papers), Non-Invasive Vital Sign Monitoring (13 papers) and IoT and Edge/Fog Computing (12 papers). Narit Hnoohom is often cited by papers focused on Context-Aware Activity Recognition Systems (30 papers), Non-Invasive Vital Sign Monitoring (13 papers) and IoT and Edge/Fog Computing (12 papers). Narit Hnoohom collaborates with scholars based in Thailand, Japan and South Korea. Narit Hnoohom's co-authors include Anuchit Jitpattanakul, Sakorn Mekruksavanich, Mahasak Ketcham, Ilsun You, Narumol Chumuang, Wantanee Kriengsinyos, Nipa Rojroongwasinkul, Virach Sornlertlamvanich, Thanaruk Theeramunkong and Pawinee Iamtrakul and has published in prestigious journals such as IEEE Access, Sensors and Applied Sciences.

In The Last Decade

Narit Hnoohom

81 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Narit Hnoohom Thailand 14 377 209 116 105 103 84 725
Frédéric Li Germany 11 256 0.7× 140 0.7× 85 0.7× 54 0.5× 119 1.2× 25 509
Stephen Xia United States 11 287 0.8× 170 0.8× 68 0.6× 41 0.4× 128 1.2× 47 715
Chintan Bhatt India 15 184 0.5× 164 0.8× 82 0.7× 59 0.6× 224 2.2× 38 931
Majid A. Al-Taee United Kingdom 18 293 0.8× 118 0.6× 148 1.3× 60 0.6× 156 1.5× 89 1.0k
Aftab Khan United Kingdom 15 233 0.6× 147 0.7× 211 1.8× 53 0.5× 111 1.1× 50 875
Kerem Altun Türkiye 6 312 0.8× 208 1.0× 66 0.6× 24 0.2× 163 1.6× 12 559
Fadi Al Machot Austria 16 327 0.9× 92 0.4× 121 1.0× 267 2.5× 168 1.6× 59 801
Hao Tian China 12 170 0.5× 121 0.6× 50 0.4× 87 0.8× 40 0.4× 27 675
Johannes Peltola Finland 8 546 1.4× 257 1.2× 166 1.4× 20 0.2× 127 1.2× 44 916
Bappaditya Mandal Singapore 17 623 1.7× 178 0.9× 29 0.3× 175 1.7× 176 1.7× 56 1.2k

Countries citing papers authored by Narit Hnoohom

Since Specialization
Citations

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

Fields of papers citing papers by Narit Hnoohom

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Narit Hnoohom

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

All Works

20 of 20 papers shown
1.
2.
Hnoohom, Narit, Sakorn Mekruksavanich, Thanaruk Theeramunkong, & Anuchit Jitpattanakul. (2024). Efficient Residual Neural Network for Human Activity Recognition using WiFi CSI Signals. 113–119. 2 indexed citations
3.
Boonsakan, Paisarn, Peti Thuwajit, Komgrid Charngkaew, et al.. (2024). Detection of centroblast cells in H&E stained whole slide image based on object detection. Frontiers in Medicine. 11. 1303982–1303982.
4.
Hnoohom, Narit, et al.. (2024). The accuracy of deep learning models for diagnosing maxillary fungal ball rhinosinusitis. European Archives of Oto-Rhino-Laryngology. 281(12). 6485–6492.
5.
Jitpattanakul, Anuchit, et al.. (2024). YOLO-Based Image Segmentation for the Diagnostic of Spondylolisthesis From Lumbar Spine X-Ray Images. IEEE Access. 12. 182242–182258. 1 indexed citations
6.
Hnoohom, Narit, Sakorn Mekruksavanich, & Anuchit Jitpattanakul. (2023). A Comprehensive Evaluation of State-of-the-Art Deep Learning Models for Road Surface Type Classification. Intelligent Automation & Soft Computing. 37(2). 1275–1291. 5 indexed citations
7.
Mekruksavanich, Sakorn, Narit Hnoohom, & Anuchit Jitpattanakul. (2023). Deep Pyramidal Residual Network for Indoor-Outdoor Activity Recognition Based on Wearable Sensor. Intelligent Automation & Soft Computing. 37(3). 2669–2686. 3 indexed citations
8.
Hnoohom, Narit, Sakorn Mekruksavanich, & Anuchit Jitpattanakul. (2023). Physical Activity Recognition Based on Deep Learning Using Photoplethysmography and Wearable Inertial Sensors. Electronics. 12(3). 693–693. 31 indexed citations
9.
Hnoohom, Narit, Sakorn Mekruksavanich, & Anuchit Jitpattanakul. (2023). Pre-Impact and Impact Fall Detection Based on a Multimodal Sensor Using a Deep Residual Network. Intelligent Automation & Soft Computing. 36(3). 3371–3385. 10 indexed citations
10.
11.
Mekruksavanich, Sakorn, et al.. (2023). Attention-Based Hybrid Deep Learning Network for Human Activity Recognition Using WiFi Channel State Information. Applied Sciences. 13(15). 8884–8884. 23 indexed citations
12.
Mekruksavanich, Sakorn, et al.. (2022). Badminton Activity Recognition and Player Assessment based on Motion Signals using Deep Residual Network. 80–83. 13 indexed citations
13.
Mekruksavanich, Sakorn, et al.. (2022). The Effect of Sensor Placement for Accurate Fall Detection based on Deep Learning Model. 124–129. 2 indexed citations
14.
Hnoohom, Narit, et al.. (2022). Visual Explanations of ResNet 101 for Blister Package Classification. 148–152. 1 indexed citations
15.
Hnoohom, Narit, Sakorn Mekruksavanich, & Anuchit Jitpattanakul. (2022). An Efficient ResNetSE Architecture for Smoking Activity Recognition from Smartwatch. Intelligent Automation & Soft Computing. 35(1). 1245–1259. 39 indexed citations
16.
Hnoohom, Narit, et al.. (2021). Feasibility Study of an Automated Carbohydrate Estimation System Using Thai Food Images in Comparison With Estimation by Dietitians. Frontiers in Nutrition. 8. 732449–732449. 11 indexed citations
17.
Mekruksavanich, Sakorn, Anuchit Jitpattanakul, & Narit Hnoohom. (2020). Negative Emotion Recognition using Deep Learning for Thai Language. 71–74. 45 indexed citations
18.
Hnoohom, Narit, et al.. (2019). Recognition Of Yoga Poses Using EMG Signals From Lower Limb Muscles. 132–136. 8 indexed citations
19.
Hnoohom, Narit, et al.. (2018). Thai fast food image classification using deep learning. 116–119. 36 indexed citations
20.
Pramkeaw, Patiyuth, Narit Hnoohom, Mahasak Ketcham, et al.. (2017). Trends in Artificial Intelligence: PRICAI 2016 Workshops. Lecture notes in computer science. 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.

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