Academic Articles & Research Papers

The use of computer vision technologies in aquaculture – A review

A review of computer vision technologies for plant phenotyping

MoringaLeafNet: A multi-class leaf disease dataset for precision agriculture and deep learning researchMendeley Data

Moringa Oleifera, which has outstanding nutritional and health benefits, is prized around the world because its leaves are rich in essential vitamins, antioxidants, and minerals that support digestion, help the immune system, and fight infl...

Aphid-ResNetSwin: An Image Recognition Method with Improved Attention Mechanism for Graded Identification of <i>Myzus persicae</i>

Myzus persicae is the most devastating piercing-sucking pest threatening tobacco production. Precise quantification of infestation severity is a prerequisite for precision pest management, making the integration of visual image analysis hig...

A Comparative Study of Physically Accurate Synthetic Shadow Datasets in Agricultural Settings with Human Activity

Shadow, a natural phenomenon resulting from the absence of light, plays a pivotal role in agriculture, particularly in processes such as photosynthesis in plants. Despite the availability of generic shadow datasets, many suffer from annotat...

Automated harvesting by a dual-arm fruit harvesting robot

Abstract In this study, we propose a method to automate fruit harvesting with a fruit harvesting robot equipped with robotic arms. Given the future growth of the world population, food shortages are expected to accelerate. Since much of Jap...

Edge-intelligent lightweight vision system for perspective-corrected egg-cage matching in cage-reared ducks

In the stereoscopic cage-rearing system, monitoring the individual egg production of laying ducks is essential for identifying low-yield individuals and optimizing breeding management. To overcome the high deployment cost of multi-sensor mo...

Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction

Abstract To predict the mechanical properties of wood in the transverse direction, this study used machine learning to extract the anatomical features of wood from cross-sectional stereograms. Specimens with different orientations of the ra...

AriAplBud: An Aerial Multi-Growth Stage Apple Flower Bud Dataset for Agricultural Object Detection Benchmarking

As one of the most important topics in contemporary computer vision research, object detection has received wide attention from the precision agriculture community for diverse applications. While state-of-the-art object detection frameworks...

An Efficient Optimization Technique for Training Deep Neural Networks

Deep learning is a sub-branch of artificial intelligence that acquires knowledge by training a neural network. It has many applications in the field of banking, automobile industry, agriculture, and healthcare industry. Deep learning has pl...

LeafNST: an improved data augmentation method for classification of plant disease using object-based neural style transfer

Abstract Plant diseases significantly threaten global agriculture, impacting crop yield and food security. Nearly 30% of the crop yield is lost due to plant diseases. Efficient identification and classification of plant diseases through com...

Computer vision technology in agricultural automation —A review

Computer vision is a field that involves making a machine “see”. This technology uses a camera and computer instead of the human eye to identify, track and measure targets for further image processing. With the development of computer visio...

Open real-time, non-invasive fish detection and size estimation utilizing binocular camera system in a Portuguese river affected by hydropeaking

The need for efficient approaches to track and assess fish behavior in rivers impacted by hydropeaking is increasing. Nonetheless, employing an automated camera system for underwater monitoring requires that the algorithms function under hi...

An Improved Convolutional Neural Network (CNN) for Disease Detection and Diagnosis for Multi-crop Plants

Agriculture is one of the largest sectors that contribute to the economic growth of countries, including Malaysia. However, plant diseases affect the quality of the harvest and impede farmers’ maximum yield output. Therefore, early detectio...

Face recognition with Bayesian convolutional networks for robust surveillance systems

Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...

An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles

In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation ...

Rapid profiling of carcinogenic types of Helicobacter pylori infection via deep learning analysis of label-free SERS spectra of human serum

WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the ...

Application of Deep Learning in Food: A Review

Deep learning has been proved to be an advanced technology for big data analysis with a large number of successful cases in image processing, speech recognition, object detection, and so on. Recently, it has also been introduced in food sci...

IoT-RiceMobileNet: An improved lightweight MobileNetV2 Model for real-time multi-class rice disease detection using IoT.

Early and real-time detection of rice leaf diseases (RLD) poses a significant challenge for farmers, especially in rural regions with limited access to advanced technology. Conventional deep learning models often require substantial computa...

Weed Detection from Unmanned Aerial Vehicle Imagery Using Deep Learning—A Comparison between High-End and Low-Cost Multispectral Sensors

In order to meet the increasing demand for crops under challenging climate conditions, efficient and sustainable cultivation strategies are becoming essential in agriculture. Targeted herbicide use reduces environmental pollution and effect...