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Pattern Recognition, Automated

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Intelligent recognition of human activities using deep learning techniques.

PloS one
Recognition of Human Actions (HAR) Portrays a crucial significance in various applications due to its ability for analyzing behaviour of humans within videos. This research investigates HAR in Red, Green, and Blue, or RGB videos using frameworks for ...

IoT powered RNN for improved human activity recognition with enhanced localization and classification.

Scientific reports
Human activity recognition (HAR) and localization are green research areas of the modern era that are being propped up by smart devices. But the data acquired from the sensors embedded in smart devices, contain plenty of noise that makes it indispens...

Deformation-invariant neural network and its applications in distorted image restoration and analysis.

Neural networks : the official journal of the International Neural Network Society
Images degraded by geometric distortions pose a significant challenge to imaging and computer vision tasks such as object recognition. Deep learning-based imaging models usually fail to give accurate performance for geometrically distorted images. In...

Feature-Tuning Hierarchical Transformer via token communication and sample aggregation constraint for object re-identification.

Neural networks : the official journal of the International Neural Network Society
Recently, transformer-based methods have shown remarkable success in object re-identification. However, most works directly embed off-the-shelf transformer backbones for feature extraction. These methods treat all patch tokens equally, ignoring the d...

A shape composition method for named entity recognition.

Neural networks : the official journal of the International Neural Network Society
Large language models (LLMs) roughly encode a sentence into a dense representation (a vector), which mixes up the semantic expression of all named entities within a sentence. So the decoding process is easily overwhelmed by sentence-specific informat...

CFI-Former: Efficient lane detection by multi-granularity perceptual query attention transformer.

Neural networks : the official journal of the International Neural Network Society
Benefiting from the booming development of Transformer methods, the performance of lane detection tasks has been rapidly improved. However, due to the influence of inaccurate lane line shape constraints, the query sequences of existing transformer-ba...

Semi-supervised non-negative matrix factorization with structure preserving for image clustering.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised learning methods have wide applications thanks to the reasonable utilization for a part of label information of data. In recent years, non-negative matrix factorization (NMF) has received considerable attention because of its interpre...

A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection.

Scientific reports
Autism Spectrum Disorder (ASD) affects approximately [Formula: see text] of the global population and is characterized by difficulties in social communication and repetitive or obsessive behaviors. Early detection of autism is crucial, as it allows t...

Repetitive training enhances the pattern recognition capability of cultured neural networks.

PLoS computational biology
Cultured neural networks in vitro have demonstrated the biocomputing capability to recognize patterns. However, the underlying mechanisms behind information processing and pattern recognition remain less understood. Here, we developed an in vitro neu...

Deep learning-based recognition model of football player's technical action behavior using PCA-LBP algorithm.

Scientific reports
Football is a sport that requires sportsmen to have both physical strength and physical features. It must consider the distinctions between individuals and then provide targeted training. Football players can perform better on the field with targeted...