Handwritten Roman characters and numbers have been intensively examined in the past several decades, with satisfactory results. The Devanagari script, however, does not fit this description. One of the most often used...
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Agriculture is an important sector of Mizoram domicile as more than half of its population relies on Agriculture as principle source of income and sustenance. Some farmers rely on the knowledge acquire from their pare...
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ISBN:
(数字)9798331523893
ISBN:
(纸本)9798331523909
Agriculture is an important sector of Mizoram domicile as more than half of its population relies on Agriculture as principle source of income and sustenance. Some farmers rely on the knowledge acquire from their parents through explicit explanation, and by observing and modelling their practices. But most farmer often struggle to understand the method and type of crops to cultivate for better crop yield. Even experienced farmer believed that using more fertilizer result in better crop yield in spite of that it damages the soil properties. To resolve this challenge, this paper presents a Crop Recommendation System using Machine Learning, tailored for Mizoram, enhancing Agriculture practices towards sustainable development. The Crop Recommendation System analyzes historical data, soil properties, weather pattern and crop performance to recommend the best crop for a specific region and its condition. The aim is to provide the Crop Recommendation System with information about the soil and the condition of the region. The study utilizes various Machine Learning Algorithms such as Random Forest, Decision Trees, Support Vector Machine and Logistic Regression to make optimal recommendation. The results indicate that Random Forest provides superior performance of 99% across all the evaluations metrics. Although many prevention measures need to be taken to avoid complications such as overfitting, etc. The overall results suggested that Random Forest achieved the best results as compared to all the other state of the art algorithms utilized with the same preprocessing steps. This approach enhances the crop and soil. After a long and often complicated process of farming method and selection of crop problem the Crop Recommendation System will aid Mizoram farmers to achieve better crops, yield and higher profit.
Brain tumor is a type of cancerous growth that may occur in the brain. Early diagnosis of the disease is crucial for proper treatment. Diagnosis of brain tumors is usually done using images obtained through magnetic r...
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Increasingly video sharing and OTT platforms aim to hyper-personalize their content for the users. This paper proposes a novel approach to dynamically recommend videos or similar events in other videos to users based ...
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Deploying a safety-critical system (SCS) adds new challenges for experts to improve system reliability, safety, and performance. Several modeling tools and techniques like Unified Modeling Language (UML), Fault Tree A...
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The Blockchain-based Internet of Things (BIoT) systems are widely used in diverse industrial fields including agriculture, healthcare, sports business, and so on. However, since the Internet of Things (IoT) devices co...
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In this paper, we propose a novel Conditional Generative Model for generating 3D point clouds using sketches as conditions. The model utilizes a sketch-time embedding extracted from sketch and timestep as conditions, ...
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ISBN:
(数字)9798331510756
ISBN:
(纸本)9798331510763
In this paper, we propose a novel Conditional Generative Model for generating 3D point clouds using sketches as conditions. The model utilizes a sketch-time embedding extracted from sketch and timestep as conditions, applying a diffusion process to noisy 3D point clouds to produce high-quality 3D models. Based on a point-voxel representation, we voxelize the point clouds and effectively integrate the sketch embedding through an improved Feature Aggregation module. Experimental results demonstrate that the proposed model outperforms existing methods in generating more precise 3D point clouds, particularly for objects with complex structures.
The sensational outcomes of machine learning (ML) are witnessed. As the big success relies on continual training with massive data encompassing sensitive information, deep neural network (DNN) models easily leak priva...
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ISBN:
(数字)9783982674100
ISBN:
(纸本)9798331534646
The sensational outcomes of machine learning (ML) are witnessed. As the big success relies on continual training with massive data encompassing sensitive information, deep neural network (DNN) models easily leak private information. For instance, large pre-trained language models contain a substantial volume of private information, which can be acquired by querying with appropriate prompts. This raises concerns regarding privacy in ML, and DNN models are evolving for privacy-preserving ML (PPML).
As computer vision technology has advanced quickly in recent years, 3D eyeball tracking and its movement have drawn the greatest attention from researchers because of its demand in screen handling and running the appl...
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Nowadays, Credit Card Frauds are one of the major fraudulent activities due to the vital increase of online payments. Credit Card Fraud generally happens when the card is stolen for any of the unauthorized purposes or...
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