274 citations · 617 across the 33 of their papers we have counts for
34 papers
Fusing Perceptual Vision Experts with Multimodal LLMs for Explainable Plant Disease Diagnosis: From Benchmark Imagery to Real-World Robotic Field Validation
Ranjan Sapkota, Konstantinos I. Roumeliotis, Pengyao Xie +3
Accurate field plant disease diagnosis requires reliable fusion of uncertain and conflicting perceptual evidence. We present the Hybrid Hierarchical Multi-Agent Framework (HM…
A Lightweight Multimodal Vision-Language Framework for Early-Stage Anatomical Green Fruit Classification in Commercial Orchards
Ranjan Sapkota, William Bu, Chen Chen +2
Accurate identification of early-stage apple fruitlet anatomical structures, including the calyx, fruitlet body, and peduncle, is essential for robotic thinning, crop-load manageme…
Optimizing YOLO27, YOLO26, YOLO11, and YOLOv8 for Fine-Grained Small-Object Detection and Segmentation in Complex Orchard Environments
Ranjan Sapkota, Manoj Karkee
This study presents an architectural and experimental cross-generation analysis of Ultralytics YOLO27 (YOLOv27), YOLO26 (YOLOv26), YOLO11 (YOLOv11), and YOLOv8 for fine-grained rob…
YOLOE-26: Integrating YOLO26 with YOLOE for Real-Time Open-Vocabulary Instance Segmentation
Ranjan Sapkota, Manoj Karkee
This paper presents YOLOE-26, a unified framework that integrates the deployment-optimized YOLO26(or YOLOv26) architecture with the open-vocabulary learning paradigm of YOLOE for r…
Generalization vs. Specialization: Evaluating Segment Anything Model (SAM3) Zero-Shot Segmentation Against Fine-Tuned YOLO Detectors
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee +1
Deep learning has advanced two fundamentally different paradigms for instance segmentation: specialized models optimized through task-specific fine-tuning and generalist foundation…
The SAM2-to-SAM3 Gap in the Segment Anything Model Family: Why Prompt-Based Expertise Fails in Concept-Driven Image Segmentation
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
This paper investigates the fundamental discontinuity between the latest two Segment Anything Models: SAM2 and SAM3. We explain why the expertise in prompt-based segmentation of SA…
Ultralytics YOLO Evolution: An Overview of YOLO27, YOLO26, YOLO11, YOLOv8, and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition
Ranjan Sapkota, Manoj Karkee
This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 thro…
Object Detection with Multimodal Large Vision-Language Models: An In-depth Review
Ranjan Sapkota, Manoj Karkee
The fusion of language and vision in large vision-language models (LVLMs) has revolutionized deep learning-based object detection by enhancing adaptability, contextual reasoning, a…
YOLO26: Key Architectural Enhancements and Performance Benchmarking for Real-Time Object Detection
Ranjan Sapkota, Rahul Harsha Cheppally, Ajay Sharda +1
This study presents a comprehensive analysis of Ultralytics YOLO26(also called as YOLOv26), highlighting its key architectural enhancements and performance benchmarking for real-ti…
Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact
Rizwan Qureshi, Ranjan Sapkota, Abbas Shah +16
Can machines truly think, reason and act in domains like humans? This enduring question continues to shape the pursuit of Artificial General Intelligence (AGI). Despite the growing…
3D Reconstruction and Information Fusion between Dormant and Canopy Seasons in Commercial Orchards Using Deep Learning and Fast GICP
Ranjan Sapkota, Zhichao Meng, Martin Churuvija +3
In orchard automation, dense foliage during the canopy season severely occludes tree structures, minimizing visibility to various canopy parts such as trunks and branches, which li…
Integrating Feature Selection and Machine Learning for Nitrogen Assessment in Grapevine Leaves using In-Field Hyperspectral Imaging
Atif Bilal Asad, Achyut Paudel, Safal Kshetri +8
Nitrogen (N) is one of the most critical nutrients in winegrape production, influencing vine vigor, fruit composition, and wine quality. Because soil N availability varies spatiall…
Agentic AI with Orchestrator-Agent Trust: A Modular Visual Classification Framework with Trust-Aware Orchestration and RAG-Based Reasoning
Konstantinos I. Roumeliotis, Ranjan Sapkota, Manoj Karkee +1
Modern Artificial Intelligence (AI) increasingly relies on multi-agent architectures that blend visual and language understanding. Yet, a pressing challenge remains: How can we tru…
UAVs Meet Agentic AI: A Multidomain Survey of Autonomous Aerial Intelligence and Agentic UAVs
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
Agentic UAVs represent a new frontier in autonomous aerial intelligence, integrating perception, decision-making, memory, and collaborative planning to operate adaptively in comple…
TRiSM for Agentic AI: A Review of Trust, Risk, and Security Management in LLM-based Agentic Multi-Agent Systems
Shaina Raza, Ranjan Sapkota, Manoj Karkee +1
Agentic AI systems, built upon large language models (LLMs) and deployed in multi-agent configurations, are redefining intelligence, autonomy, collaboration, and decision-making ac…
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
This review presents a comprehensive analysis of two emerging paradigms in AI-assisted software development: vibe coding and agentic coding. While both leverage large language mode…
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
Ranjan Sapkota, Konstantinos I. Roumeliotis, Manoj Karkee
This review critically distinguishes between AI Agents and Agentic AI, offering a structured, conceptual taxonomy, application mapping, and analysis of opportunities and challenges…
Vision-Language-Action (VLA) Models: Concepts, Progress, Applications and Challenges
Ranjan Sapkota, Yang Cao, Konstantinos I. Roumeliotis +1
Vision-Language-Action (VLA) models mark a transformative advancement in artificial intelligence, aiming to unify perception, natural language understanding, and embodied action wi…
Design, Integration, and Evaluation of a Dual-Arm Robotic System for High Throughput Tissue Sampling from Potato Tubers
Divyanth L. G., Syed Usama Bin Sabir, Divya Rathore +3
Manual tissue extraction from potato tubers for molecular pathogen detection is highly laborious. This study presents a machine-vision-guided, dual-arm coordinated inline robotic s…
Plant Disease Detection through Multimodal Large Language Models and Convolutional Neural Networks
Konstantinos I. Roumeliotis, Ranjan Sapkota, Manoj Karkee +2
Automation in agriculture plays a vital role in addressing challenges related to crop monitoring and disease management, particularly through early detection systems. This study in…
A Review of 3D Object Detection with Vision-Language Models
Ranjan Sapkota, Konstantinos I Roumeliotis, Rahul Harsha Cheppally +2
This review provides a systematic analysis of comprehensive survey of 3D object detection with vision-language models(VLMs) , a rapidly advancing area at the intersection of 3D vis…
RF-DETR Object Detection vs YOLOv12 : A Study of Transformer-based and CNN-based Architectures for Single-Class and Multi-Class Greenfruit Detection in Complex Orchard Environments Under Label Ambiguity
Ranjan Sapkota, Rahul Harsha Cheppally, Ajay Sharda +1
This study conducts a detailed comparison of RF-DETR object detection base model and YOLOv12 object detection model configurations for detecting greenfruits in a complex orchard en…
An Integrated Visual Servoing Framework for Precise Robotic Pruning Operations in Modern Commercial Orchard
Dawood Ahmed, Basit Muhammad Imran, Martin Churuvija +1
This study presents a vision-guided robotic control system for automated fruit tree pruning applications. Traditional pruning practices are labor-intensive and limit agricultural e…
Improved YOLOv12 with LLM-Generated Synthetic Data for Enhanced Apple Detection and Benchmarking Against YOLOv11 and YOLOv10
Ranjan Sapkota, Manoj Karkee
This study evaluated the performance of the YOLOv12 object detection model, and compared against the performances YOLOv11 and YOLOv10 for apple detection in commercial orchards bas…