Tomorn Soontornnapar- Master of Engineering
- Lecturer at Siam University
Tomorn Soontornnapar
- Master of Engineering
- Lecturer at Siam University
About
7
Publications
313
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Introduction
Electrical and AI Researcher in the field of Industrial and Healthcare applications.
Skills and Expertise
Current institution
Publications
Publications (7)
This paper proposes an end-to-end pipeline to detect broken eggs in a holder without extensive training, employing a two-step image segmentation and processing approach using saliency scores, all without relying on a large amount of labeled data. The process begins by inputting an egg image with text prompts into Grounding DINO, which returns an eg...
This study presents a novel approach to eggshell crack detection by integrating zero-shot learning with advanced image analysis techniques. The proposed method utilizes a hybrid dataset composed of a custom hen egg collection—50 tray images containing 30 eggs each arranged in a 6×5 grid—and the Botta et al. duck egg dataset, comprising approximatel...
![Experimental test cases from the HIFD dataset [22]: Six types of falls...](publication/387225391/figure/fig1/AS:11431281308722755@1739069730019/Experimental-test-cases-from-the-HIFD-dataset-22-Six-types-of-falls-and-thirteen-types_Q320.jpg)
The ability to accurately detect and classify falls is critical for ensuring timely medical intervention, especially for the elderly, who face a significantly higher risk of severe injuries, loss of independence, or fatal outcomes from falls. This paper introduces a novel fall detection approach that addresses these urgent needs by using short-time...
This paper presents a reliable energy baseline model for self-benchmarking evaluation of energy saving potential by using multilayer perceptron (MLP) method. The measured energy data and product quantities of the sample plant in daily period dating back since 2011 to 2016 are used as variables and then normalized to represent the energy baseline (E...
One use of evolutionary computational approaches, generalized regression neural networks (GRNNs) in mean curve approximation of lightning impulse waveforms is presented. This paper explores in-depth details on artificial neural nets (ANNs) especially in biased term and probabilistic transfer function adapted with special linear layer. Evaluation in...
