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A comparative analysis of deep learning methods for weed classification of high-resolution UAV images
Because weeds compete directly with crops for moisture, nutrients, space, and sunlight, their monitoring and control is an essential necessity in...
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Optimizing diabetes classification with a machine learning-based framework
BackgroundDiabetes is a metabolic disorder usually caused by insufficient secretion of insulin from the pancreas or insensitivity of cells to...
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Classification of strawberry ripeness stages using machine learning algorithms and colour spaces
Accurate classification of strawberry ripeness is a crucial aspect of ensuring high-quality food products, optimizing harvesting and storage...
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Improving Deep Learning-based Plant Disease Classification with Attention Mechanism
In recent years, deep learning-based plant disease classification has been widely developed. However, it is challenging to collect sufficient...
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Matchtigs: minimum plain text representation of k-mer sets
We propose a polynomial algorithm computing a minimum plain-text representation of k -mer sets, as well as an efficient near-minimum greedy heuristic....
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Asking the right questions for mutagenicity prediction from BioMedical text
Assessing the mutagenicity of chemicals is an essential task in the drug development process. Usually, databases and other structured sources for...
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Hybrid deep learning approach to improve classification of low-volume high-dimensional data
BackgroundThe performance of machine learning classification methods relies heavily on the choice of features. In many domains, feature generation...
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Centrifuger: lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification
Centrifuger is an efficient taxonomic classification method that compares sequencing reads against a microbial genome database. In Centrifuger, the...
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Noisecut: a python package for noise-tolerant classification of binary data using prior knowledge integration and max-cut solutions
BackgroundClassification of binary data arises naturally in many clinical applications, such as patient risk stratification through ICD codes. One of...
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Accelerometer sampling requirements for animal behaviour classification and estimation of energy expenditure
BackgroundBiologgers have contributed greatly to studies of animal movement, behaviours and physiology. Accelerometers, among the various on-board...
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HAHNet: a convolutional neural network for HER2 status classification of breast cancer
ObjectiveBreast cancer is a significant health issue for women, and human epidermal growth factor receptor-2 (HER2) plays a crucial role as a vital...
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Multinomial classification of NLRP3 inhibitory compounds based on large scale machine learning approaches
The role of NLRP3 inflammasome in innate immunity is newly recognized. The NLRP3 protein is a family of nucleotide-binding and oligomerization...
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Investigation of bacterial DNA gyrase Inhibitor classification models and structural requirements utilizing multiple machine learning methods
Infections from multidrug-resistant (MDR) bacteria have emerged as a paramount global health concern, and the therapeutic effectiveness of current...
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Adap-BDCM: Adaptive Bilinear Dynamic Cascade Model for Classification Tasks on CNV Datasets
Copy number variation (CNV) is an essential genetic driving factor of cancer formation and progression, making intelligent classification based on...
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Dendritic SE-ResNet Learning for Bioinformatic Classification
The construction of neural networks is a widely adopted approach in deep learning for tackling classification problems, aiming to emulate the...
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Optimizing Potato Disease Classification Using a Metaheuristics Algorithm for Deep Learning: A Novel Approach for Sustainable Agriculture
Potato is a food crop at a global scale, bearing a hefty importance for the food security and nutrition of millions of people worldwide. Nonetheless,...
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BMRI-NET: A Deep Stacked Ensemble Model for Multi-class Brain Tumor Classification from MRI Images
Brain tumors are one of the most dangerous health problems for adults and children in many countries. Any failure in the diagnosis of brain tumors...
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Sequence-Based Classification and Identification
You will be introduced to the classification of prokaryotes from species to the higher levels of class and phyla. You will learn that the 16S rRNA...
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Fine-grained image classification on bats using VGG16-CBAM: a practical example with 7 horseshoe bats taxa (CHIROPTERA: Rhinolophidae: Rhinolophus) from Southern China
BackgroundRapid identification and classification of bats are critical for practical applications. However, species identification of bats is a...
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Temporal classification of short time series data
MotivationWithin the frame of their genetic capacity, organisms are able to modify their molecular state to cope with changing environmental...
