AIMC Topic: Algorithms

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PiTLiD: Identification of Plant Disease From Leaf Images Based on Convolutional Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
With the development of plant phenomics, the identification of plant diseases from leaf images has become an effective and economic approach in plant disease science. Among the methods of plant diseases identification, the convolutional neural networ...

MV-H-RKM: A Multiple View-Based Hypergraph Regularized Restricted Kernel Machine for Predicting DNA-Binding Proteins.

IEEE/ACM transactions on computational biology and bioinformatics
DNA-binding proteins (DBPs) have a significant impact on many life activities, so identification of DBPs is a crucial issue. And it is greatly helpful to understand the mechanism of protein-DNA interactions. In traditional experimental methods, it is...

A Multi-Attention Approach for Person Re-Identification Using Deep Learning.

Sensors (Basel, Switzerland)
Person re-identification (Re-ID) is a method for identifying the same individual via several non-interfering cameras. Person Re-ID has been felicitously applied to an assortment of computer vision applications. Due to the emergence of deep learning a...

Report on the AAPM deep-learning spectral CT Grand Challenge.

Medical physics
BACKGROUND: This Special Report summarizes the 2022 AAPM Grand Challenge on Deep-Learning spectral Computed Tomography (DL-spectral CT) image reconstruction.

Evaluating the generalizability of deep learning image classification algorithms to detect middle ear disease using otoscopy.

Scientific reports
To evaluate the generalizability of artificial intelligence (AI) algorithms that use deep learning methods to identify middle ear disease from otoscopic images, between internal to external performance. 1842 otoscopic images were collected from three...

Application of symmetry evaluation to deep learning algorithm in detection of mastoiditis on mastoid radiographs.

Scientific reports
As many human organs exist in pairs or have symmetric appearance and loss of symmetry may indicate pathology, symmetry evaluation on medical images is very important and has been routinely performed in diagnosis of diseases and pretreatment evaluatio...

Are Deep Neural Networks Adequate Behavioral Models of Human Visual Perception?

Annual review of vision science
Deep neural networks (DNNs) are machine learning algorithms that have revolutionized computer vision due to their remarkable successes in tasks like object classification and segmentation. The success of DNNs as computer vision algorithms has led to ...

Cell damage evaluation by intelligent imaging flow cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Essential thrombocythemia (ET) is an uncommon situation in which the body produces too many platelets. This can cause blood clots anywhere in the body and results in various symptoms and even strokes or heart attacks. Removing excessive platelets usi...

Differential evolution based dual adversarial camouflage: Fooling human eyes and object detectors.

Neural networks : the official journal of the International Neural Network Society
Deep neural network-based object detectors are vulnerable to adversarial examples. Among existing works to fool object detectors, the camouflage-based method is more often adopted due to its adaptation to multi-view scenarios and non-planar objects. ...

Artificial Intelligence for Neuroimaging and Musculoskeletal Radiology: Overview of Current Commercial Algorithms.

Seminars in roentgenology
There is a rapidly increasing number of artificial intelligence (AI) products cleared by the Food and Drug Administration (FDA) for quantification, identification, and even diagnosis in clinical radiology. This review article aims to summarize the la...