AIMC Topic: Recognition, Psychology

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A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost.

Science advances
Neuromodulators in the brain act globally at many forms of synaptic plasticity, represented as metaplasticity, which is rarely considered by existing spiking (SNNs) and nonspiking artificial neural networks (ANNs). Here, we report an efficient brain-...

A novel feature-scrambling approach reveals the capacity of convolutional neural networks to learn spatial relations.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) are one of the most successful computer vision systems to solve object recognition. Furthermore, CNNs have major applications in understanding the nature of visual representations in the human brain. Yet it remain...

Aphid cluster recognition and detection in the wild using deep learning models.

Scientific reports
Aphid infestation poses a significant threat to crop production, rural communities, and global food security. While chemical pest control is crucial for maximizing yields, applying chemicals across entire fields is both environmentally unsustainable ...

Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model.

Sensors (Basel, Switzerland)
Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When a sign language user intera...

Edge detection using fast pixel based matching and contours mapping algorithms.

PloS one
Current methods of edge identification were constrained by issues like lighting changes, position disparity, colour changes, and gesture variability, among others. The aforementioned modifications have a significant impact, especially on scaled facto...

Spatial oblivion channel attention targeting intra-class diversity feature learning.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural networks (CNNs) have successfully driven many visual recognition tasks including image classification. However, when dealing with classification tasks with intra-class sample style diversity, the network tends to be disturbed by ...

GACN: Generative Adversarial Classified Network for Balancing Plant Disease Dataset and Plant Disease Recognition.

Sensors (Basel, Switzerland)
Plant diseases are a critical threat to the agricultural sector. Therefore, accurate plant disease classification is important. In recent years, some researchers have used synthetic images of GAN to enhance plant disease recognition accuracy. In this...

Hybrid convolution neural network with channel attention mechanism for sensor-based human activity recognition.

Scientific reports
In the field of machine intelligence and ubiquitous computing, there has been a growing interest in human activity recognition using wearable sensors. Over the past few decades, researchers have extensively explored learning-based methods to develop ...

Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition.

Neural networks : the official journal of the International Neural Network Society
Event-based visual, a new visual paradigm with bio-inspired dynamic perception and μs level temporal resolution, has prominent advantages in many specific visual scenarios and gained much research interest. Spiking neural network (SNN) is naturally s...

Transformer-based hand gesture recognition from instantaneous to fused neural decomposition of high-density EMG signals.

Scientific reports
Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a Compact Transformer-based Hand Gestu...