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FedSHE: privacy preserving and efficient federated learning with adaptive segmented CKKS homomorphic encryption
Unprotected gradient exchange in federated learning (FL) systems may lead to gradient leakage-related attacks. CKKS is a promising approximate...
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A deep dive into enhancing sharing of naturalistic driving data through face deidentification
Human factors research in transportation relies on naturalistic driving studies (NDS) which collect real-world data from drivers on actual roads. NDS...
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From single to universal: tiny lesion detection in medical imaging
Accurate and automatic detection of tiny lesions in medical imaging plays a critical role in comprehensive cancer diagnosis, staging, treatment,...
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Diagnosing Dementia Disorder Detection Using an Improved Eliminate Particle Swarm Optimization (IEPSO) Based on Convolutional Neural Networks
Dementia is an un-repairable and continuous disease that affects a person's mental health. Symptoms of Dementia may vary from one person to another,...
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Challenges to Applying Role Playing in Software Engineering Education: A Taxonomy Derived from a Rapid Literature Review
Role Playing (RP) serves as an instructional approach to enrich the learning experience for students and boost their learning by the effective...
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Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression
Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique to activate or inhibit the activity of neurons, and thereby...
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A hybrid neural network for urban rail transit short-term flow prediction
Accurate and rapid short-term passenger flow prediction is the foundation for safe and efficient operation of urban rail transit systems. The urban...
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A robust two-step algorithm for community detection based on node similarity
The rapid development of the internet and social network platforms has given rise to a new field of research, social network analysis. This field of...
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Transfer learning for emotion detection in conversational text: a hybrid deep learning approach with pre-trained embeddings
Understanding the emotions and sentiments from conversations has relevance in many application areas. Specifically, conversational agents,...
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Early Diagnosis of COVID-19 Disease by ChestNet Convolutional Neural Network from Chest Xray Images
In the absence of a vaccine, prompt isolation and medical care are necessary to prevent and contain the COVID-19 pandemic. This requires a quick and...
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Cleaning ECG with Deep Learning: A Denoiser Tested in Industrial Settings
As the popularity of wearables continues to scale, a substantial portion of the population has now access to (self-)monitorization of cardiovascular...
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Neural Networks and the Nonlinear Feynman–Kac Theorem Applied to Financial Options Pricing
The classic financial market model proposed by Black and Scholes allows solving, under a series of simplifying assumptions, the problem of valuing...
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Transmission-guided multi-feature fusion Dehaze network
Image dehazing is an important direction of low-level visual tasks, and its quality and efficiency directly affect the quality of high-level visual...
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Real-time salient object detection based on accuracy background and salient path source selection
Boundary and connectivity prior are common methods for detecting the image salient object. They often address two problems: 1) if the salient object...
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A privacy-preserving image retrieval scheme with access control based on searchable encryption in media cloud
With the popularity of the media cloud computing industry, individuals and organizations outsource image computation and storage to the media cloud...
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Blind Color Image Watermarking Using Deep Artificial Neural Network Using Statistical Features
With increasing digital content over the internet it is very important to secure the digital contents in such a way that the identity and integrity...
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SKGDC: Effective Segmentation Based Deep Learning Methodology for Banana Leaf, Fruit, and Stem Disease Prediction
In agriculture, detecting plant diseases is crucial for optimal plant growth. Initially, input images are collected from three datasets: banana leaf...
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Deep attentive multimodal learning for food information enhancement via early-stage heterogeneous fusion
In contrast to single-modal content, multimodal data can offer greater insight into food statistics more vividly and effectively. But traditional...
