AIMC Topic: Neural Networks, Computer

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Plant Disease Recognition: A Large-Scale Benchmark Dataset and a Visual Region and Loss Reweighting Approach.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Plant disease diagnosis is very critical for agriculture due to its importance for increasing crop production. Recent advances in image processing offer us a new way to solve this issue via visual plant disease analysis. However, there are few works ...

Human-scale Brain Simulation via Supercomputer: A Case Study on the Cerebellum.

Neuroscience
Performance of supercomputers has been steadily and exponentially increasing for the past 20 years, and is expected to increase further. This unprecedented computational power enables us to build and simulate large-scale neural network models compose...

Passive filter design for fractional-order quaternion-valued neural networks with neutral delays and external disturbance.

Neural networks : the official journal of the International Neural Network Society
The problem on passive filter design for fractional-order quaternion-valued neural networks (FOQVNNs) with neutral delays and external disturbance is considered in this paper. Without separating the FOQVNNs into two complex-valued neural networks (CV...

Automatic detection of seafloor marine litter using towed camera images and deep learning.

Marine pollution bulletin
Aerial and underwater imaging is being widely used for monitoring litter objects found at the sea surface, beaches and seafloor. However, litter monitoring requires a considerable amount of human effort, indicating the need for automatic and cost-eff...

Prediction of adverse drug reactions using drug convolutional neural networks.

Journal of bioinformatics and computational biology
Prediction of Adverse Drug Reactions (ADRs) has been an important aspect of Pharmacovigilance because of its impact in the pharma industry. The standard process of introduction of a new drug into a market involves a lot of clinical trials and tests. ...

Deep Learning Regression for Prostate Cancer Detection and Grading in Bi-Parametric MRI.

IEEE transactions on bio-medical engineering
One of the most common types of cancer in men is prostate cancer (PCa). Biopsies guided by bi-parametric magnetic resonance imaging (MRI) can aid PCa diagnosis. Previous works have mostly focused on either detection or classification of PCa from MRI....

Automated Classification and Segmentation in Colorectal Images Based on Self-Paced Transfer Network.

BioMed research international
Colorectal imaging improves on diagnosis of colorectal diseases by providing colorectal images. Manual diagnosis of colorectal disease is labor-intensive and time-consuming. In this paper, we present a method for automatic colorectal disease classifi...

Bidirectional Interaction Network for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Person re-identification (ReID) task aims to retrieve the same person across multiple spatially disjoint camera views. Due to huge image changes caused by various factors such as posture variation and illumination transformation, images of different ...

Automated Bone Age Assessment Using Artificial Intelligence: The Future of Bone Age Assessment.

Korean journal of radiology
Bone age assessments are a complicated and lengthy process, which are prone to inter- and intra-observer variabilities. Despite the great demand for fully automated systems, developing an accurate and robust bone age assessment solution has remained ...

Artificial immune system features added to breast cancer clinical data for machine learning (ML) applications.

Bio Systems
We here propose a new method of combining a mathematical model that describes a chemotherapy treatment for breast cancer with a machine-learning (ML) algorithm to increase performance in predicting tumor size using a five-step procedure. The first st...