AIMC Topic: Neural Networks, Computer

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Lightweight image super-resolution based multi-order gated aggregation network.

Neural networks : the official journal of the International Neural Network Society
Recently, Transformer-based models are taken much focus on solving the task of image super-resolution (SR) due to their ability to achieve better performance. However, these models combined huge computational cost during the computing self-attention ...

Toward Intrinsic Adversarial Robustness Through Probabilistic Training.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Modern deep neural networks have made numerous breakthroughs in real-world applications, yet they remain vulnerable to some imperceptible adversarial perturbations. These tailored perturbations can severely disrupt the inference of current deep learn...

Binding the Person-Specific Approach to Modern AI in the Human Screenome Project: Moving past Generalizability to Transferability.

Multivariate behavioral research
Advances in ability to comprehensively record individuals' digital lives and in AI modeling of those data facilitate new possibilities for describing, predicting, and generating a wide variety of behavioral processes. In this paper, we consider these...

Cell recognition based on atomic force microscopy and modified residual neural network.

Journal of structural biology
Cell recognition methods are in high demand in cell biology and medicine, and the method based on atomic force microscopy (AFM) shows a great value in application. The difference in mechanical properties or morphology of cells has been frequently use...

Video-Based Human Activity Recognition Using Deep Learning Approaches.

Sensors (Basel, Switzerland)
Due to its capacity to gather vast, high-level data about human activity from wearable or stationary sensors, human activity recognition substantially impacts people's day-to-day lives. Multiple people and things may be seen acting in the video, disp...

Deep Learning-Based Computational Cytopathologic Diagnosis of Metastatic Breast Carcinoma in Pleural Fluid.

Cells
A Pleural effusion cytology is vital for treating metastatic breast cancer; however, concerns have arisen regarding the low accuracy and inter-observer variability in cytologic diagnosis. Although artificial intelligence-based image analysis has show...

Interpretable deep learning for improving cancer patient survival based on personal transcriptomes.

Scientific reports
Precision medicine chooses the optimal drug for a patient by considering individual differences. With the tremendous amount of data accumulated for cancers, we develop an interpretable neural network to predict cancer patient survival based on drug p...

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

IEEE transactions on biomedical circuits and systems
Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulat...

A 0.99-to-4.38 uJ/class Event-Driven Hybrid Neural Network Processor for Full-Spectrum Neural Signal Analyses.

IEEE transactions on biomedical circuits and systems
Versatile and energy-efficient neural signal processors are in high demand in brain-machine interfaces and closed-loop neuromodulation applications. In this paper, we propose an energy-efficient processor for neural signal analyses. The proposed proc...

Extended performance analysis of deep-learning algorithms for mice vocalization segmentation.

Scientific reports
Ultrasonic vocalizations (USVs) analysis represents a fundamental tool to study animal communication. It can be used to perform a behavioral investigation of mice for ethological studies and in the field of neuroscience and neuropharmacology. The USV...