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Agriculture

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Leveraging three-tier deep learning model for environmental cleaner plants production.

Scientific reports
The world's population is expected to exceed 9 billion people by 2050, necessitating a 70% increase in agricultural output and food production to meet the demand. Due to resource shortages, climate change, the COVID-19 pandemic, and highly harsh soci...

Advanced deep learning techniques for early disease prediction in cauliflower plants.

Scientific reports
Agriculture plays a pivotal role in the economies of developing countries by providing livelihoods, sustenance, and employment opportunities in rural areas. However, crop diseases pose a significant threat to both farmers' incomes and food security. ...

Amharic political sentiment analysis using deep learning approaches.

Scientific reports
This study delves into the realm of sentiment analysis in the Amharic language, focusing on political sentences extracted from social media platforms in Ethiopia. The research employs deep learning techniques, including Convolutional Neural Networks ...

Multispectral Plant Disease Detection with Vision Transformer-Convolutional Neural Network Hybrid Approaches.

Sensors (Basel, Switzerland)
Plant diseases pose a critical threat to global agricultural productivity, demanding timely detection for effective crop yield management. Traditional methods for disease identification are laborious and require specialised expertise. Leveraging cutt...

LULC change detection using support vector machines and cellular automata-based ANN models in Guna Tana watershed of Abay basin, Ethiopia.

Environmental monitoring and assessment
Recurrent changes recorded in LULC in Guna Tana watershed are a long-standing problem due to the increase in urbanization and agricultural lands. This research aims at identifying and predicting frequent changes observed using support vector machines...

Role of modeling and artificial intelligence in process parameter optimization of biochar: A review.

Bioresource technology
Enhancement of crop yield, conservation and quality upgradation of soil, and efficient water management are the main objectives of sustainable agriculture and mitigating climate change's impact on agriculture. In recent days, biochar, obtained via th...

Based on the multi-scale information sharing network of fine-grained attention for agricultural pest detection.

PloS one
It is of great significance to identify the pest species accurately and control it effectively to reduce the loss of agricultural products. The research results of this project will provide theoretical basis for preventing and controlling the spread ...

Neuromorphic sequence learning with an event camera on routes through vegetation.

Science robotics
For many robotics applications, it is desirable to have relatively low-power and efficient onboard solutions. We took inspiration from insects, such as ants, that are capable of learning and following routes in complex natural environments using rela...

Large-scale automatic extraction of agricultural greenhouses based on high-resolution remote sensing and deep learning technologies.

Environmental science and pollution research international
Widely used agricultural greenhouses are critical in the development of facility agriculture because of not only their huge capacity in food and vegetable supplies, but also their environmental and climatic effects. Therefore, it is important to obta...

Real-Time Detection of Strawberry Ripeness Using Augmented Reality and Deep Learning.

Sensors (Basel, Switzerland)
Currently, strawberry harvesting relies heavily on human labour and subjective assessments of ripeness, resulting in inconsistent post-harvest quality. Therefore, the aim of this work is to automate this process and provide a more accurate and effici...