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Article
Open AccessChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review
ChatGPT is another large language model (LLM) vastly available for the consumers on their devices but due to its performance and ability to converse effectively, it has gained a huge popularity amongst researc...
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Article
Triage of potential COVID-19 patients from chest X-ray images using hierarchical convolutional networks
The current COVID-19 pandemic has motivated the researchers to use artificial intelligence techniques for a potential alternative to reverse transcription-polymerase chain reaction due to the limited scale of ...
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Article
VIRFIM: an AI and Internet of Medical Things-driven framework for healthcare using smart sensors
After affecting the world in unexpected ways, the virus has started mutating which is evident with the insurgence of its new variants. The governments, hospitals, schools, industries, and humans, in general, a...
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Article
Skeleton-based human action recognition with sequential convolutional-LSTM networks and fusion strategies
Human action recognition from skeleton data has drawn a lot of attention from researchers due to the availability of thousands of real videos with many challenges. Existing works attempted to model the spatial...
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Article
Q-learning and LSTM based deep active learning strategy for malware defense in industrial IoT applications
Edge devices are extensively used as intermediaries between the device and the service layer in an industrial Internet of things (IIoT) environment. These devices are quite vulnerable to malware attacks. Exist...
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Article
Toward soft real-time stress detection using wrist-worn devices for human workspaces
Continuous exposure to stress leads to many health problems and substantial economic loss in companies. A lot of attention has been given to the development of wearable systems for stress monitoring to tackle ...
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Article
Open AccessCAPHAR: context-aware personalized human activity recognition using associative learning in smart environments
The existing action recognition systems mainly focus on generalized methods to categorize human actions. However, the generalized systems cannot attain the same level of recognition performance for new users m...
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Article
Hybrid and hierarchical fusion networks: a deep cross-modal learning architecture for action recognition
Two-stream networks have provided an alternate way of exploiting the spatiotemporal information for action recognition problem. Nevertheless, most of the two-stream variants perform the fusion of homogeneous m...
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Article
Semantic Image Networks for Human Action Recognition
In this paper, we propose the use of a semantic image, an improved representation for video analysis, principally in combination with Inception networks. The semantic image is obtained by applying localized sp...
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Article
A framework for retinal vessel segmentation from fundus images using hybrid feature set and hierarchical classification
Retinal blood vessels play an imperative role in detection of many ailments, such as cardiovascular diseases, hypertension, and diabetic retinopathy. The automated way of segmenting vessels from retinal images...
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Chapter and Conference Paper
A Novel Curvature Feature Embedded Level Set Method for Image Segmentation of Coronary Angiograms
Segmentation methods in medical image processing are usually distorted by low contrast and intensity inhomogeneity. There are several image segmentation methods which are based on region based segmentation. B...