作者：
Warbhe, Mohan K.Bore, Joy JordanChaudari, Shiv Nath
Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Sawangi Wardha442001 India
Faculty of Engineering and Technology Department of Computer Science and Medical Engineering MaharashtraSawangi Wardha442001 India
The proposed web application for tomato leaf disease detection exemplifies the transformative power of Artificial Intelligence and computer Vision in modern agriculture. Addressing the critical issue of early and accu...
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Obtaining high-quality remote sensing images is crucial in generating a three-dimensional terrain for flight simulators. However, due to the presence of haze and other impact factors, collected remote sensing images u...
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The proceedings contain 77 papers. The topics discussed include: advanced optimization techniques for electric vehicle integrated solar-hydro-thermal systems;lowering the peak to average power ratio by using the pts m...
ISBN:
(纸本)9798331513894
The proceedings contain 77 papers. The topics discussed include: advanced optimization techniques for electric vehicle integrated solar-hydro-thermal systems;lowering the peak to average power ratio by using the pts method for high-speed applicationsystems;impact of atmospheric turbidity on terahertz communication in tropical sub-continent;solar energy based cogeneration system for improved solar energy utilization;vision transformers for retinal disease classification using optical coherence tomography images;a classification approach to UPI transaction efficiency and its impact on microbusinesses in digital India;optimal power dispatch in combined heat and power systems with solar and wind integration;and optimization of cluster head selection using bacterial foraging algorithm for energy-efficient routing in wireless body area networks.
This paper presents a novel application of multimodal large language models (LLMs) to enhance the learning and application of building energy modeling. The study leverages Retrieval-Augmented Generation (RAG) models i...
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This paper presents a novel application of multimodal large language models (LLMs) to enhance the learning and application of building energy modeling. The study leverages Retrieval-Augmented Generation (RAG) models integrated with a dataset of 59 publicly available YouTube video tutorials focused on EnergyPlus and OpenStudio. Unlike traditional LLM methods, this approach is unique in its utilization of three LLMs to process and integrate different types of data: text, screenshots, and video references. The preprocessing phase utilizes Google's transcription service to convert video content into text, which is then summarized using the T5 model and embedded with the Instructor Embedder model. Meta's Llama v2 7b model handles user queries, extracting relevant information and providing detailed responses enriched with visual references, including exact video minutes and screenshots. Unlike traditional LLM models, the proposed model delivers comprehensive responses that go beyond text, providing users with reference videos with exact timestamps and screenshots. Furthermore, the proposed web interface presents these enriched responses in one page, significantly reducing the time needed for users to understand and apply complex energy modeling concepts. This framework demonstrates the potential of multimodal LLMs in creating powerful educational tools for architects, engineers, and students. The entire workflow was completed on a laptop with a single 4GB GPU, demonstrating the feasibility of implementing such a system on relatively modest hardware.
Smart applications are getting more powerful and cheaper cost due to the advancement in sensor technology. In this chapter, we have considered a smart greenhouse application. The important parameters of the smart gree...
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Traditional battery maintenance methods have some problems, such as low efficiency, difficult to find potential problems in time and accurately, which affect the stability and reliability of power system. This paper s...
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[Objective] This study aims to design an automatic agricultural machinery identification system based on computer vision, to address the issue of disorganized and chaotic labeling of some agricultural machinery produc...
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Models based on machine learning are optimization models that collect data, assess it, and deliver the reports required by specialists and management to make the best decisions. The application of contemporary machine...
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This research aims to analyze the satisfaction of staff members at the Faculty of Dentistry, University of Phayao, regarding the use of applicationsystems that support business processes, focusing on the data archite...
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Users often begin exploratory visual analysis (EVA) without clear analysis goals but iteratively refine them as they learn more about their data. As an essential step in data science, researchers want to aid EVA by de...
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