Arshleen Kaur

422 citations
80 papers · 234 · h-index 8

Impact in

Papers in

Co-authors
Vinay Kukreja (64 shared papers)Rishabh Sharma (59 shared papers)Manisha Aeri (15 shared papers)Deepak Upadhyay (8 shared papers)Mukesh Kumar (8 shared papers)Manika Manwal (11 shared papers)Ankur Choudhary (8 shared papers)Deepak Banerjee (3 shared papers)
Journals
Current Medicinal Chemistry (1 paper)Biomedical Signal Processing and Control (1 paper)International Conference on Computing, Communication, and Intelligent Systems (ICCCIS) (1 paper)IEEE International Conference for Convergence in Technology (I2CT) (9 papers)IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) (16 papers)
Partner nations
IndiaUnited Arab Emirates

In The Last Decade

Arshleen Kaur

67 papers receiving 219 citations

Peers

Arshleen Kaur
Comparison fields: 5 of 48
  • Health Informatics 7
  • Plant Science 87
  • Computer Vision and Pattern Recognition 36
  • Marketing 13
  • Industrial and Manufacturing Engineering 12
Replace Md. Kafil Uddin with:
Md. Kafil Uddin Bangladesh
Chengxin Liu China
Germán H. Alférez Spain
R. M. Kapila Tharanga Rathnayaka Sri Lanka
Noureddine Falih Morocco
Priyanka P. Shinde India
Yaw Marfo Missah Ghana
Vazeerudeen Abdul Hameed Malaysia
I Putu Agung Bayupati Indonesia
Abhishek Kaushik Ireland
Arshleen Kaur relative to Md. Kafil Uddin Bangladesh Md. Kafil Uddin's profile →
Citations per field
00.5×5×10×13×
Md. Kafil Uddin · 1×
Citations per year

Countries citing papers authored by Arshleen Kaur

Since Specialization
Citations

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

Fields of papers citing papers by Arshleen Kaur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Arshleen Kaur, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Arshleen Kaur Line = papers co-authored together Arshleen Kaur links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1
An Efficient Fine-tuned GoogleNet Model for Multiclass Classification of Blood Cell Cancer
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Nitin Thapliyal, Manika Manwal, Rishabh Sharma
202413
2
MintLeafNet: A CNN Model for Accurate and Efficient Detection of Multiple Mint Leaf Diseases
IEEE Global Conference for Advancement in Technology (GCAT) ·Arshleen Kaur, Vinay Kukreja, Deepak Banerjee, Karun Madan
202312
3
Integrating Convolutional Neural Networks and Random Forest for Accurate Grading of Rice Spot Disease Severity
International Conference for Emerging Technology (INCET) ·Arshleen Kaur, Rishabh Sharma, Deepak Upadhyay, Manisha Aeri
202410
4
DeepCitrus: Leveraging Integrated CNN and VGG16 for Automated Orange Leaf Disease Detection
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Deepak Upadhyay, Manisha Aeri, Rishabh Sharma
20249
5
RetDense: A Fine-tuned DenseNet121 Model for Retinal Eye Disease Detection
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Mukesh Kumar, Ankur Choudhary, Rishabh Sharma
20249
6
A Fine-Tuned DenseNet Model for an Efficient Maize Leaf Disease Classification
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Mukesh Kumar, Ankur Choudhary, Rishabh Sharma
20248
7
Empowering Wildlife Conservation with a Fused CNN-SVM Deep Learning Model for Multi-Classification Using Drone-Based Imagery
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Saumitra Chattopadhyay, Aditya Verma, Rishabh Sharma
20248
8
A Fine-tuned Deep Learning-based VGG16 Model for Cotton Leaf Disease Classification
International Conference for Emerging Technology (INCET) ·Arshleen Kaur, Vinay Kukreja, Mukesh Kumar, Ankur Choudhary, Rishabh Sharma
20248
9
Advanced Disease Management: An Encoder-Decoder Approach for Tomato Black Mold Detection
IEEE Pune Section International Conference (PuneCon) ·Arshleen Kaur, Vinay Kukreja, Sushant Chamoli, Siddhant Thapliyal, Rishabh Sharma
20237
10
Automated Mango Rust Severity Classification: A CNN-SVM Ensemble Approach for Accurate and Granular Disease Assessment in Mango Cultivation
Arshleen Kaur, Vinay Kukreja, Nisha Chandran S, Navin Garg, Rishabh Sharma
20236
11
An Integrated GoogleNet with Convolutional Neural Networks Model for Multiclass Bean Leaf Lesion Detection
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Deepak Upadhyay, Manisha Aeri, Rishabh Sharma
20246
12
Innovative Hybrid Framework for Precise Wheat Disease Identification: Stacked CNN Meets SVM
Arshleen Kaur, Vinay Kukreja, Deepak Banerjee, Satvik Vats
20235
13
Advanced Multi-Scale Classification of Onion Smut Disease Using a Hybrid CNN-RF Ensemble Model for Precision Agriculture
Arshleen Kaur, Vinay Kukreja, Sushant Chamoli, Siddhant Thapliyal, Rishabh Sharma
20235
14
Rice Sheath Rot Disease Detection and Severity Classification: A Novel Framework Leveraging CNN-LSTM Models for Multi-Classification
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Sonal Malhotra, Kireet Joshi, Rishabh Sharma
20245
15
Amplifying Apple Mosaic Illness Detection: Combining CNN and Random Forest Models
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Priyanshi Aggarwal, Siddhant Thapliyal, Rishabh Sharma
20245
16
Unveiling Kale Diversity in Indian Agriculture: CNN - Logistic Regression Classification
International Conference for Emerging Technology (INCET) ·Arshleen Kaur, Rishabh Sharma, Deepak Singh Rana, Ashish Garg
20245
17
ResPoultry: An Enhanced ResNet50 Model for Multiclass Classification of Poultry Diseases
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Deepak Upadhyay, Manisha Aeri, Rishabh Sharma
20244
18
An Effective Pistachio Classification by Ensembling Fine-tuned ResNet20 and DenseNet Models
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Deepak Upadhyay, Manisha Aeri, Rishabh Sharma
20244
19
Multi-class Guava Disease Classification using an Efficient and Fine-Tuned DenseNet model
IEEE International Conference for Convergence in Technology (I2CT) ·Arshleen Kaur, Vinay Kukreja, Deepak Upadhyay, Manisha Aeri, Rishabh Sharma
20244
20
Fruitful Fusion: An Accuracy-Boosting Ensemble of VGG19 and Convolutional Neural Networks for Dragon Fruit Classification
IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI) ·Arshleen Kaur, Vinay Kukreja, Manika Manwal, Rishabh Sharma +1 other
20244

About Arshleen Kaur

Arshleen Kaur is a scholar working on Plant Science, Computer Vision and Pattern Recognition, Artificial Intelligence, Health Information Management and Computational Theory and Mathematics, having authored 80 papers that have together received 234 indexed citations. Recurring topics across this work include Smart Agriculture and AI (60 papers), Advanced Neural Network Applications (8 papers), AI in cancer detection (3 papers), Emotion and Mood Recognition (2 papers), Artificial Intelligence in Healthcare (2 papers), Explainable Artificial Intelligence (XAI) (2 papers), Computational Drug Discovery Methods (2 papers) and Retinal Imaging and Analysis (1 paper). The work is most often cited by research in Health Informatics (7 citations), Plant Science (87 citations), Computer Vision and Pattern Recognition (36 citations), Marketing (13 citations) and Industrial and Manufacturing Engineering (12 citations). Arshleen Kaur has collaborated with scholars based in India and United Arab Emirates. Frequent co-authors include Vinay Kukreja, Rishabh Sharma, Manisha Aeri, Deepak Upadhyay, Mukesh Kumar, Manika Manwal, Ankur Choudhary, Deepak Banerjee, Kireet Joshi and Garima Verma. Their work appears in journals such as Current Medicinal Chemistry, Biomedical Signal Processing and Control, International Conference on Computing, Communication, and Intelligent Systems (ICCCIS), IEEE International Conference for Convergence in Technology (I2CT) and IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI).

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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