Rajmeet Singh

FRAISE-Net: Scale-aware attention and adaptive cross-scale fusion for strawberry disease inspection

Asim Ali Khan, Rajmeet Singh, Samee U. Khan, Dwarikanath Mahapatra et autres

Early and reliable detection of strawberry foliar diseases is essential for reducing yield loss, limiting unnecessary pesticide use, and supporting timely site-specific crop management. This paper presents FRAISE-Net , a one-stage Strawberry Disease Inspection Network for automated localization and recognition of strawberry …

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Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

Manveen Kaur, Rajmeet Singh, Saeed Mozaffri, Shahpour Alirezaee

Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measurement with thread or caliper is accurate but infeasible at commercial scale. This paper presents CucumberVision, a non-contact length estimation framework using an Intel …

Curvature-aware 3D length estimation of greenhouse cucumbers using RGB-D imaging and cubic spline arc-length integration

Manveen Kaur, Rajmeet Singh, Saeed Mozaffri, Shahpour Alirezaee

Commercial greenhouse cucumber production is graded by fruit length, which drives harvest scheduling, labour allocation, and logistics. Manual measurement with thread or caliper is accurate but infeasible at commercial scale. This paper presents CucumberVision, a non-contact length estimation framework using an Intel …

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Deep RL- Tuned Mo del-Free Adaptive Control for Lower-Limb Exoskeletons During Sit-to-Stand Transitions

Ranjeet Kumbhar, Appaso M Gadade, Rajmeet Singh, Ashish Singla et autres

Sit-to-stand (STS) transitions impose significant joint-loading demands on elderly individuals, making them a primary target for lower-limb exoskeleton assistance. However, accurate trajectory tracking during STS is challenging due to complex, time-varying human exoskeleton interaction dynamics and inter-subject variability that render model-based control …

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YOLO26-RipeLoc Lite: A lightweight architecture for tomato ripeness detection and picking point localization in greenhouse robotic harvesting

Rajmeet Singh, Manveen Kaur, Shahpour Alirezaee, Irfan Hussain

In greenhouse tomato production, automated harvesting requires accurate detection of ripe tomatoes, ripeness classification, and precise picking-point localization for robotic end-effectors. This paper proposes YOLO26-RipeLoc Lite, a lightweight deep learning architecture based on YOLO26 for simultaneous detection, ripeness classification, and center-point localization …

YOLO26-RipeLoc Lite: A lightweight architecture for tomato ripeness detection and picking point localization in greenhouse robotic harvesting

Rajmeet Singh, Manveen Kaur, Shahpour Alirezaee, Irfan Hussain

In greenhouse tomato production, automated harvesting requires accurate detection of ripe tomatoes, ripeness classification, and precise picking-point localization for robotic end-effectors. This paper proposes YOLO26-RipeLoc Lite, a lightweight deep learning architecture based on YOLO26 for simultaneous detection, ripeness classification, and center-point localization …

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Sensitivity-driven deep learning model for tribological prediction in Al7075/B4C nanocomposites

Ranjeet Kumbhar, Rajmeet Singh, Appaso M. Gadade

Abstract The development of lightweight, durable composites for industrial use is constrained by traditional tribological evaluation methods that are costly, time-consuming, and inadequate for capturing nonlinear interactions between material and operational parameters. This study proposes an integrated framework combining Global Sensitivity Analysis …

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YOLOv8-PnP fusion architecture for non-contact robotic pollination: a 6D pose estimation approach for autonomous greenhouse operations

Rajmeet Singh, Manveen Kaur, Appaso M. Gadade, Irfan Hussain

Background: The declining availability of natural pollinators and limitations of contact-based robotic pollination methods including flower damage, pathogen transmission, and reduced operational efficiency necessitate innovative solutions for protected horticulture. Gap: Existing robotic pollinators achieve limited success rates (∼ 66%) primarily due to …

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Sensitivity-Driven Deep Learning Model for Tribological Prediction in Al7075/B4C Nanocomposites

Ranjeet Kumbhar, Rajmeet Singh, Appaso Gadade, Divyanshi R. Kumar et autres

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Towards smart farming: a real-time diagnosis system for strawberry foliar diseases using deep learning

Asim Ali Khan, Rajmeet Singh, Samee U. Khan, Irfan Hussain

BACKGROUND: Developing an effective machine vision system is crucial to successfully deploying robotic inspection in open field conditions and controlled environments like greenhouses. Robotic arms with vision-based deep learning models offer an efficient, real-time, non-invasive crop monitoring solution. In agricultural settings, they …

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A comprehensive review of current robot-based pollinators for crop pollination

Rajmeet Singh, Lakmal D. Seneviratne, Irfan Hussain

The decline of bee and wind-based pollination systems in greenhouses due to controlled environments and limited access has boosted the importance of finding alternative pollination methods. Robot-based pollination systems have emerged as a promising solution, ensuring adequate crop yield even in challenging …

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Visual-language transformer-based tomato leaf disease detection for portable greenhouse monitoring device

Manveen Kaur, Rajmeet Singh, Shahpour Alirezaee, Irfan Hussain

Tomato leaf diseases pose a significant threat to global food security, necessitating accurate and efficient detection methods. This paper introduces the Tomato Leaf Disease Visual Language Model (TLDVLM), a novel approach based on the BLIP-2 architecture enhanced with Low-Rank Adaptation (LoRA), for …

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