Search
38 articles for “food images”
-
Deep Plate: A Deep Learning Approach to Recipe Generation from Food Images
Abstract: In the deep learning era, image understanding is advancing in sophistication, encompassing both semantic interpretation and the generation of meaningful image descriptions. To achieve this, deep neural networks must undergo specific cross-model training; these networks must be both simple enough to handle a wide range of inputs and complex enough to encode the fine contextual information associated with the image. An appropriate example of the previously described picture comprehension problem …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 2, 2024 · pp. 15–22 Read article
-
Depiction-inspired Recipe Generator Using Deep Learning
Abstract: Machine learning has become a crucial part of modern life, influencing various domains. Its applications range from enhancing data-driven business decisions to enabling autonomous vehicles. Advances in machine learning have brought about notable changes in how we interact with technology. In the culinary world, the idea of creating food recipes from images has gained increasing interest. This entails the development of innovative systems that seamlessly convert visual input, such as …
Published in Journal of Open Source Developments · Vol. 11, Issue 2, 2024 · pp. 47–55 Read article
-
Hyperspectral Image Compression and Classification: A Survey
Abstract: The applications of hyperspectral images (HSI) are many, which include agriculture, food quality, remote sensing, medical diagnostics and safety assessment. Hyperspectral image analysis has been used for detecting contaminants and identifying defects in food. It also utilizes advanced software and hardware tools hence allowing users to diagnose and detect pathologies. In this paper an avant-garde investigation about Hyperspectral image compression and classification techniques which can be used in various applications …
Published in Journal of Remote Sensing & GIS Read article
-
Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article
-
AI Chatbot for Expressing Visual Content
Abstract: Recently, the artificial intelligence (AI) chatbot for expressing visual content has shown remarkable multi-modal capabilities. It can recognize funny features in photos and create webpages straight from handwritten text. These characteristics are uncommon in earlier vision language models. We think the use of a more sophisticated large language model (LLM) is the main factor behind vision verbalizer's superior multi-modal generating capabilities. We introduce vision verbalizer, which employs a single projection …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 11–19 Read article
-
Tomato Food Delivery
Abstract: Tomato food delivery systems face numerous challenges, such as duplicate documents, lack of security, and insufficient transparency. This paper proposes a solution using the MERN (MongoDB, Express.js, React, Node.js) stack to address these issues by creating an electronic public administration system that ensures secure, transparent, and efficient record-keeping. Leveraging MongoDB, the proposed system, automates the maintenance of records and registration documents, utilizing a consensus-based contract for streamlined loan settlement processes …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 1, 2025 · pp. 12–19 Read article
-
The Effect of Packaging Design Elements on Purchase Intention of Junk Food Among College Students
Abstract: This research investigates the impact of packaging design elements on the purchase intention of junk food among college students. Recognizing the influence of visual appeal on consumer behavior, particularly within young adult demographics, this study aims to identify which specific packaging elements, such as color, imagery, typography, and branding, resonate most with college students when choosing junk food. A descriptive survey method was used, targeting students in Delhi NCR, with …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 14, Issue 3, 2024 · pp. 39–47 Read article
-
Calorie Measurement and Food Recognition Using Machine Learning
Abstract: Nowadays, all over the world most people are suffering from different types of diseases or obesity. This is because of bad food habits or eating food without knowing the calorie and other sources from the foods. Precise techniques for gauging food and energy consumption play a vital role in addressing obesity. Offering users or patients accessible and smart solutions to assess their food intake and gather dietary information constitute valuable …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 1–9 Read article
-
Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
-
Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 Read article
-
Smart Agriculture in India: Advancements in Image Processing for Automated Plant Disease Detection and Crop Analysis
Abstract: The adoption of image processing technologies in agriculture is emerging as a revolutionary method for tackling persistent challenges in the farming industry. These techniques are increasingly used for different tasks such as detecting plant diseases, assessing crop health, and predicting yields, especially in the framework of smart agriculture systems. This study paints a detailed picture of the latest progress in image processing techniques applied to automated disease detection and detailed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 13–19 Read article
-
Food Insecurity: A Growing Threat to Nigeria’s National Security
Abstract: In Nigeria, the topic of food security has played a significant role in the national security equation. The study argues that though the strategic conception and approach are important in the articulation of threats analysis, the non-strategic conceptions like food security or insecurity are also important. It also examines the1erformance of this sector and the extent to which it could be employed as a catalyst to the defence of national …
Published in Recent Trends in Social Studies · Vol. 1, Issue 2, 2024 · pp. 57–65 Read article
-
Crop Disease Prediction by Machine Learning
Abstract: The classification of Crop can be classified into several methods. The data set of crop leaf illnesses, notably Bacterial Leaf Blight disease (BLB), a crop leaf disease with significant outbreaks throughout Thailand, and Brown Spot Crop disease (BSR), is classified employing image classification in this study. Additionally, image processing technology is used for identifying different types of crop leaf disease. These algorithms include the Random Forest, Decision Tree, Gradient Boost, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 21–25 Read article
-
Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture
Abstract: Farming Forward: Integrating IoT, AI, and Image Processing for Sustainable Agriculture" explores the convergence of cutting-edge technologies in revolutionizing traditional farming practices towards sustainability. This study investigates the integration of Internet of Things (IoT), Artificial Intelligence (AI), and Image Processing techniques in agricultural contexts, aiming to enhance efficiency, productivity, and environmental stewardship. Through a comprehensive review of recent advancements and case studies, this research elucidates the transformative potential of IoT-enabled …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 52–69 Read article
-
An AAV Vector for Inducible Gene Expression Preferentially in Muscles
Abstract: Adeno associated viral (AAV) vectors has been used widely in gene therapy and efforts have been made to improve their utility by adding genetic elements that would enable targeting transgene expression to particular cells or tissues of interest and permitting on/off regulation of expression. In this study, we designed a recombinant AAV9 variant PHP.eB vector with muscle creatine kinase (Mck)-derived enhancers, a synthetic muscle-expression promoter, in combination with a third-generation …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 1, Issue 2, 2023 · pp. 46–61 Read article
-
A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
-
Development and Characterization of Antimicrobial Polymer Composites for Food Packaging Applications
Abstract: The increasing demand for sustainable and antimicrobial food packaging materials has led to extensive research in polymer-based composites. This study focuses on developing a polyethylene terephthalate-ethylene vinyl acetate (PET-EVA) composite reinforced with metal oxide nanoparticles (MONs), including Cu₂O, ZnO, and MgO₂. These nanoparticles were selected for their antimicrobial properties and ability to enhance the functional characteristics of the composite. Structural, chemical, mechanical, and barrier properties were extensively evaluated to determine …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 86–93 Read article
-
Identification of Papaya Fruit Ripening Process Using AI
Abstract: Identifying the ripening process of papaya fruit using artificial intelligence involves employing machine learning algorithms to analyze various features such as color changes, texture alterations and chemical compositions. This model is capable of analyzing visual cues to determine the stage of ripeness. The dataset compares images of papaya at various ripening stages, and our AI model demonstrated high accuracy in classifying these stages. Employing machine learning algorithms and image processing …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 13, Issue 2, 2024 · pp. 23–30 Read article
-
The Role of IoT in Sustainable Agriculture: Leveraging Big Data for Precision Farming
Abstract: Precision farming combined with the Internet of Things (IoT) is transforming the agricultural industry by boosting productivity and encouraging sustainable practices.. This paper explores the transformative impact of IoT technologies on modern agriculture, focusing on how big data analytics can be leveraged to optimize farming practices, reduce waste, and conserve resources. The Internet of Things (IoT) offers real-time data on a range of agricultural characteristics, including soil moisture, temperature, humidity, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
-
Intelligent Machine for Food Quality and Safety Assessment
Abstract: This paper presents the development of an intelligent fruit and vegetable classification system aimed at reducing food waste and infections caused by spoiled items. Using artificial intelligence and sensor data, our system classifies items into three categories: ripe, unripe, and rotten, and employs servo motors to sort them into respective baskets. The classification process utilizes real-time temperature, humidity, and image data captured by the camera and processed by the laptop. …
Published in International Journal of Industrial and Product Design Engineering · Vol. 2, Issue 1, 2024 · pp. 24–28 Read article