AIMC Topic: Deep Learning

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MaskMol: knowledge-guided molecular image pre-training framework for activity cliffs with pixel masking.

BMC biology
BACKGROUND: Activity cliffs, which refer to pairs of molecules that are structurally similar but show significant differences in their potency, can lead to model representation collapse and make the model challenging to distinguish them.

Multi-branch and multi-label tree species classification using deep learning for UAV aerial photography and Sentinel remote sensing images.

Scientific reports
The classification and identification of forest tree species is of great value in the study of species diversity and forest monitoring. With the development of emerging technologies, the combination of remote sensing images and deep learning methods ...

Searching for effective preprocessing method and CNN based architecture with efficient channel attention on speech emotion recognition.

Scientific reports
Recently, Speech emotion recognition (SER) performance has steadily increased as multiple deep learning architectures have adapted. Especially, convolutional neural network (CNN) models with spectrogram data preprocessing are the most popular approac...

Progress, challenges and future of linguistic neural decoding with deep learning.

Communications biology
Language is the primary medium through which humans achieve information transfer and exchange. It enables the conveyance of ideas, concepts, and messages, thereby playing an indispensable role in social interaction and knowledge dissemination. Lingui...

RCANE: a deep learning algorithm for whole-genome pan-cancer somatic copy number aberration prediction using RNA-seq data.

Communications biology
Transcriptome sequencing (RNA-seq) of cancers is widely employed in cancer research to investigate gene expression patterns and their role in disease progression. Somatic copy-number aberrations (SCNAs)-critical genomic drivers of tumorigenesis-can a...

Deep fusion based transfer learning with bald eagle search algorithm for sign language recognition to assist individuals with hearing and speech impairments.

Scientific reports
Sign language (SL) is a significant communication method for individuals with hearing impairments, using hand gestures to convey letters, words, and sentences. However, several people are unfamiliar with SL, creating a communication gap. An intellige...

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.

Nature communications
Data-driven approaches have advanced colorectal lesion diagnosis in digestive endoscopy, yet their application in endocytoscopy (EC)-a high-magnification imaging technique-remains limited, with most studies relying on conventional machine learning me...

A novel hybrid deep learning model for segmentation and uzzy Res-LeNet based classification for Alzheimer's disease.

Neurogenetics
Alzheimer's disease (AD) is a progressive illness that can cause behavioural abnormalities, personality changes, and memory loss. Early detection helps with future planning for both the affected person and caregivers. Thus, an innovative hybrid Deep ...

Prediction of high-performing spleen-targeted lipid nanoparticles using a deep learning model for robust anticancer immunotherapy.

Journal of materials chemistry. B
Messenger RNA (mRNA) therapeutics hold significant potential across a wide range of medical applications. LNPs are the most clinically advanced mRNA delivery vehicles, but challenges such as off-target effects and liver accumulation limit their broad...

Water meter reading recognition method based on character attention mechanism.

PloS one
With the rapid advancement of computer vision technology, traditional manual methods of reading meters are increasingly being replaced by automated water meter reading technologies based on image recognition. This technology can precisely locate and ...