PFDI: a precise fruit disease identification model based on context data fusion with faster-CNN in edge computing environment

Article Engineering, Multidisciplinary

New York City taxi trip duration prediction using MLP and XGBoost

M. Poongodi et al.

Summary: Predicting the duration and price of taxi trips through apps like Ola and Uber can help users plan their trips properly, reserve time margins for potential traffic congestions, and assist drivers in selecting faster routes.

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT (2022)

添加到收藏夹

Article Mathematics

Enhanced Convolutional Neural Network Model for Cassava Leaf Disease Identification and Classification

Umesh Kumar Lilhore et al.

Summary: This study proposes a comprehensive learning strategy for real-time Cassava leaf disease identification based on an enhanced CNN model. The experimental results show that the proposed ECNN model performs well on a balanced dataset, improving classification performance.

MATHEMATICS (2022)

添加到收藏夹

Article Computer Science, Information Systems

A deep learning approach to intelligent fruit identification and family classification

Nehad M. Ibrahim et al.

Summary: Deep learning techniques have been successfully applied to the identification and classification of fruits. A novel Convolutional Neural Network (CNN) model was proposed in this study to extract fruit features and classify them into different families. The results showed that the CNN model achieved higher accuracy and efficiency compared to other models such as ResNet-20 and SVM.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

添加到收藏夹

Article Chemistry, Analytical

Smart Strawberry Farming Using Edge Computing and IoT

Mateus Cruz et al.

Summary: Strawberries are sensitive fruits that require intensive use of agrochemicals and pesticides due to pest and disease issues. A developed IoT platform integrates monitoring services for environmental and crop data analysis, while using a computer vision model for real-time disease detection. The system also supports long-distance data transmission using LoRa communication and machine learning capabilities for outlier detection. These technologies together aim to mitigate disease problems and environmental damage in strawberry farming.

SENSORS (2022)

添加到收藏夹

Article

An Improved EfficientNetV2 Model Based on Visual Attention Mechanism: Application to Identification of Cassava Disease

Yuanbo Ye et al.

Computational Intelligence and Neuroscience (2022)

添加到收藏夹

Article Mathematical & Computational Biology

A Framework for Interactive Medical Image Segmentation Using Optimized Swarm Intelligence with Convolutional Neural Networks

Chetna Kaushal et al.

Summary: Recent technological advancements have greatly impacted various image processing applications, including medical imaging. Segmentation of diagnostic images using deep learning algorithms is crucial for identifying regions of interest. This study proposes a pipeline for image segmentation using traditional Convolutional Neural Networks (CNNs) and Swarm Intelligence (SI) for optimal identification of desired areas. Various modules, including Fuzzy C-means (FCM), K-means, and different improvisations with Particle Swarm Optimization (PSO) and CNNs, are examined and evaluated. Experimental analysis on different types of medical images shows that K-means with CNN achieves the best performance with 96.45% segmentation accuracy and an average time of 9.09 seconds.

COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE (2022)

添加到收藏夹

Article Computer Science, Information Systems

Hybridized approach of image segmentation in classification of fruit mango using BPNN and discriminant analyzer

Neeraj Kumari et al.

Summary: This paper focuses on improving image classification accuracy by determining defected areas of mangoes using image segmentation algorithm and utilizing Enhanced Fuzzy based K-means clustering algorithm and Backpropagation Based Discriminant Classifier. The image features are extracted using geometric, texture, and color-based methods, with feature selection done by Maximally Correlated Principal Component Analysis. The proposed model achieves the highest accuracy when compared with existing methods, classifying images into three categories: good quality, average quality, and poor quality mangoes.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

添加到收藏夹

Article Computer Science, Information Systems

The fruit classification algorithm based on the multi-optimization convolutional neural network

Xiao Chen et al.

Summary: This study proposes a fruit image classification method based on multi-optimization convolutional neural network, utilizing wavelet threshold for denoising and gamma transform for image correction. SOM network is introduced for pre-learning, and a comprehensive optimization model of convolution and full connection is established for feature extraction and regression classification, achieving an accuracy of 99% in fruit classification.

MULTIMEDIA TOOLS AND APPLICATIONS (2021)

添加到收藏夹

Article

Diagnosis and combating COVID-19 using wearable Oura smart ring with deep learning methods

M. Poongodi et al.

Personal and Ubiquitous Computing (2021)

添加到收藏夹

Article Engineering, Electrical & Electronic

A probabilistic segmentation and entropy-rank correlation-based feature selection approach for the recognition of fruit diseases

Muhammad Attique Khan et al.

Summary: Agriculture is vital in some countries' economies, but plant and fruit diseases cause significant losses to farmers. This study proposes an automated system for identifying fruit diseases with high accuracy.

EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING (2021)

添加到收藏夹

Article Computer Science, Hardware & Architecture