Amogh Joshi
Agricultural and Biological Sciences · Purdue University West Lafayette
Publications
21
Citations
57
Est. group size
—
Recurring co-author estimate
Active years
9
Publishing since 2017
Amogh Joshi's work applies machine learning and computer vision to agricultural problems, such as building large-scale image datasets for classifying crops and weeds and creating tools for annotating agricultural images. Other publications show broader work in machine learning applications, including analyzing political imagery online, image stitching/view synthesis, and use of language models, suggesting an interdisciplinary computing background applied across multiple domains including agriculture.
Publication output was minimal or absent in the earlier part of the decade but has grown noticeably since 2021, peaking in 2023-2025.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- iNatAg: Multi-Class Classification Models Enabled by a Large-Scale Benchmark Dataset with 4.7M Images of 2,959 Crop and Weed Species
arXiv (Cornell University) · 2025
- iNatAg: Multi-Class Classification Models Enabled by a Large-Scale Benchmark Dataset with 4.7M Images of 2,959 Crop and Weed Species
2025
- Prediction of Headache Improvement Using Multimodal Machine Learning in Patients with Acute Post-traumatic Headache (P5-12.002)
Neurology · 2024
- Examining Similar and Ideologically Correlated Imagery in Online Political Communication
Proceedings of the International AAAI Conference on Web and Social Media · 2024
- Neural Light Spheres for Implicit Image Stitching and View Synthesis
2024
- Automated Generation and Evaluation of MultipleChoice Quizzes using Langchain and Gemini LLM
2024
- Pathfinding Visualizer: A Survey of the State-of-Art
Lecture notes in networks and systems · 2023
- An Open Source Simulation Toolbox for Annotation of Images and Point Clouds in Agricultural Scenarios
Lecture notes in computer science · 2023
- An Algorithmic Approach for Text Summarization
2023
- Standardizing and Centralizing Datasets for Efficient Training of Agricultural Deep Learning Models
Plant Phenomics · 2023
- Exploiting the Right: Inferring Ideological Alignment in Online Influence Campaigns Using Shared Images
arXiv (Cornell University) · 2022
- Standardizing and Centralizing Datasets to Enable Efficient Training of Agricultural Deep Learning Models
arXiv (Cornell University) · 2022
- Examining Similar and Ideologically Correlated Imagery in Online Political Communication
arXiv (Cornell University) · 2021
- Future of Cybersecurity: A Study on Biometric Scans
International Journal for Research in Applied Science and Engineering Technology · 2021
- Correlating vapour-liquid equilibria of binary HI + H2O mixtures using Pitzer’s model of electrolyte solutions
Separation and Purification Technology · 2017
- arXiv (Cornell University)×7
- Plant Phenomics×1
- Separation and Purification Technology×1
- International Journal for Research in Applied Science and Engineering Technology×1
- Proceedings of the International AAAI Conference on Web and Social Media×1
- Changye Yang
Agricultural and Biological Sciences · Purdue University West Lafayette
- Bruce Erickson
Agricultural and Biological Sciences · Purdue University West Lafayette
- Aaron Ault
Agricultural and Biological Sciences · Purdue University West Lafayette
- Andrew Balmos
Agricultural and Biological Sciences · Purdue University West Lafayette
- Chen‐Yi Lu
Agricultural and Biological Sciences · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile