Exploring the landscape of automated species identification apps: Development, promise, and user appraisal
Two decades ago, Gaston and O'Neill (2004) deliberated on why automated species
identification had not become widely employed. We no longer have to wonder: This AI …
identification had not become widely employed. We no longer have to wonder: This AI …
[HTML][HTML] Overview of pest detection and recognition algorithms
B Guo, J Wang, M Guo, M Chen, Y Chen, Y Miao - Electronics, 2024 - mdpi.com
Detecting and recognizing pests are paramount for ensuring the healthy growth of crops,
maintaining ecological balance, and enhancing food production. With the advancement of …
maintaining ecological balance, and enhancing food production. With the advancement of …
ML‐DDoSnet: IoT intrusion detection based on denial‐of‐service attacks using machine learning methods and NSL‐KDD
The Internet of Things (IoT) is a complicated security feature in which datagrams are
protected by integrity, confidentiality, and authentication services. The network is protected …
protected by integrity, confidentiality, and authentication services. The network is protected …
Multi-objective SHADE with manta ray foraging optimizer for structural design problems
This paper presents a hybrid multi-objective success history-based parameter adaptive
differential evolution (SHADE) with manta ray foraging optimizer (MRFO) for structural …
differential evolution (SHADE) with manta ray foraging optimizer (MRFO) for structural …
Butterflies recognition using enhanced transfer learning and data augmentation
HT Adityawan, O Farroq, S Santosa… - Journal of …, 2023 - dl.futuretechsci.org
Butterflies' recognition serves a crucial role as an environmental indicator and a key factor in
plant pollination. The automation of this recognition process, facilitated by Convolutional …
plant pollination. The automation of this recognition process, facilitated by Convolutional …
Quantum healthcare computing using precision based granular approach
Previously, doctors interpreted diseases and their outcomes according to their experience in
diagnosis. However, with the rapid increase in technology and population, the task of …
diagnosis. However, with the rapid increase in technology and population, the task of …
[PDF][PDF] Large-scale insect pest image classification
TN Doan - Journal of Advances in Information Technology, 2023 - jait.us
One of the main issues with agricultural production is insect attack, which leads to poor crop
quality. Farmers, however, have a complicated and time-consuming task in detecting and …
quality. Farmers, however, have a complicated and time-consuming task in detecting and …
Big Data Analytics Using Artificial Intelligence
Data analytics using artificial intelligence is the process of leveraging advanced AI
techniques to extract insights and knowledge from large and complex datasets [1]. This …
techniques to extract insights and knowledge from large and complex datasets [1]. This …
Investigation of Applying Machine Learning and Hyperparameter Tuned Deep Learning Approaches for Arrhythmia Detection in ECG Images
The level of patient's illness is determined by diagnosing the problem through different
methods like physically examining patients, lab test data, and history of patient and by …
methods like physically examining patients, lab test data, and history of patient and by …
Fusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System
A Thakkar, N Kikani, R Geddam - Applied Soft Computing, 2024 - Elsevier
Securing networks is becoming increasingly crucial due to the widespread use of
information technology. Intrusion Detection System (IDS) plays a crucial role in network …
information technology. Intrusion Detection System (IDS) plays a crucial role in network …